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How Recruiting Automation is changing the talent game

Hiring has always been a challenge, but in today’s competitive market, it feels tougher than ever. The best candidates often juggle multiple offers, and companies that move too slowly lose out. On top of that, recruiters spend hours on repetitive work — scanning resumes, coordinating interviews, chasing paperwork.
Author
Medha Bisht
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November 18, 2025
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3 min read

Why recruiting automation matters today

Hiring has always been a challenge, but in today’s competitive market, it feels tougher than ever. The best candidates often juggle multiple offers, and companies that move too slowly lose out. On top of that, recruiters spend hours on repetitive work — scanning resumes, coordinating interviews, chasing paperwork.

This is where recruiting automation steps in. What was once considered a niche HR tool has now become a business essential. Done right, automation doesn’t replace human recruiters. Instead, it makes them more effective by freeing them from manual tasks so they can focus on building relationships and making smarter hiring decisions.

What recruiting automation really means

At its core, recruiting automation uses technology to handle tasks that recruiters traditionally did by hand. Think of activities like sourcing candidates, screening resumes, scheduling interviews, sending reminders, or even creating onboarding documents.

This idea is part of a bigger trend called hyperautomation, where multiple technologies like AI, machine learning, and robotic process automation come together to streamline entire workflows. In recruiting, it means integrating tools so that everything from finding talent to managing employee records connects smoothly. The real power lies in building an end-to-end system where data flows seamlessly across HR and business platforms. This way, hiring isn’t just a standalone process but part of the organization’s larger growth strategy.

How AI recruiting automation delivers results

The business case for AI recruiting automation isn’t just about saving effort — it’s about measurable returns.

Cutting time-to-hire

Speed is critical. The average time-to-hire in 2025 is 36 days, which leaves plenty of room for improvement. Companies like United HR Solutions showed how AI platforms reduced time-to-hire by 45% and time-to-fill by 47%. In many cases, automation slashes hiring time by 30–50%.

When candidates receive faster responses and quick offers, companies avoid losing them to competitors. This also reduces the cost of vacant positions and boosts candidate satisfaction.

Reducing cost-per-hire

Hiring is expensive. Globally, the average cost per hire is around $4,683 when factoring in ads, recruiter hours, and agency fees. Manual scheduling alone can eat up five hours per candidate.

Automation cuts these costs significantly. Studies show administrative overhead can drop by up to 80%. Some reports estimate that AI recruiters can save as much as $16,000 per hire, thanks to faster shortlisting and reduced manual screening.

Another advantage: while manual costs rise with the number of hires, automated systems stay stable, making them ideal for fast-growing companies.

Improving candidate quality

Automation also raises the bar on candidate quality. AI tools focus on skills and experience, reducing unconscious bias and creating a fairer process. Resume-screening accuracy can reach 85–95%, far higher than manual reviews.

Case studies show a 40% boost in candidate quality scores and a 36% rise in sourcing quality after automation. Hiring better-fit employees lowers turnover, saving money and building stronger teams.

Enhancing candidate experience

Today’s candidates expect fast, transparent communication. Automation ensures they get it. Chatbots answer questions 24/7, automated emails provide updates, and scheduling tools let candidates book interviews at their convenience.

Companies using these tools report a 49% drop in candidate drop-off and a 44% increase in satisfaction. For example, the American Heart Association doubled its sourcing activity and boosted recruiter engagement by 50% after cutting administrative work with automation.

Smarter tools: the HackerEarth example

Automation isn’t one-size-fits-all. Some platforms are designed for specific industries. HackerEarth, for instance, specializes in tech hiring.

Best practices for recruiting automation

Adopting recruiting automation requires more than just buying software. Success depends on strategy and people.

Choosing the right platform

Pick tools that are scalable, easy to use, and able to integrate with your HR stack. 

Building seamless integrations

An Applicant Tracking System (ATS) often serves as the hub. The best setups integrate with CRMs, payroll, and learning platforms. Tools like Zapier help connect different apps into a unified workflow.

Managing change and training teams

Resistance is common. Recruiters may worry about losing relevance or struggling with new tools. The solution is open communication and involvement. Bringing teams into the process early can increase adoption success rates. Hands-on training and continuous learning opportunities ease fears and ensure recruiters can fully use the new system.

The future of recruiting automation

The new Role of recruiters

Contrary to fears, AI will not replace recruiters. Instead, it will reshape their role. The best outcomes will come from a human-AI hybrid model. Recruiters will be able to focus more on relationship-building, candidate engagement, and employer branding, while automation provides efficiency and insights. Those who embrace this partnership will be the most successful in the talent market of the future.

Conclusion: The smarter way forward

Recruiting automation is no longer optional. It speeds up hiring, cuts costs, improves candidate quality, and enhances the overall experience. It’s about creating a partnership where automation handles the repetitive work, and recruiters focus on what they do best: building connections and making smart, strategic choices.

As competition for talent grows, the companies that thrive will be the ones that adopt automation thoughtfully and use it to empower their people. The message is clear: the future of hiring is human and automated — working together to create stronger, smarter organizations.

FAQs on recruiting automation

How does automation improve candidate experience?

By giving faster responses, consistent updates, and convenient scheduling. Chatbots answer questions anytime, and candidates can book interviews without delays. This respect for their time builds trust and strengthens employer branding.

Can automation replace human recruiters?

No. Automation is great for repetitive, high-volume tasks like screening or scheduling. But recruiters bring empathy, judgment, and cultural insight that machines can’t replicate. The future is about working together, not replacement.

How I used VibeCode Arena platform to build code using AI and learnt how to improve it

How a developer used VibeCoding to generate Image Carousal code using VibeCode Arena platform and used objective evaluations to improve the LLM generated code
Author
Vineet Khandelwal
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November 8, 2025
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3 min read

I Used AI to Build a "Simple Image Carousel" at VibeCodeArena. It Found 15+ Issues and Taught Me How to Fix Them.

My Learning Journey

I wanted to understand what separates working code from good code. So I used VibeCodeArena.ai to pick a problem statement where different LLMs produce code for the same prompt. Upon landing on the main page of VibeCodeArena, I could see different challenges. Since I was interested in an Image carousal application, I picked the challenge with the prompt "Make a simple image carousel that lets users click 'next' and 'previous' buttons to cycle through images."

Within seconds, I had code from multiple LLMs, including DeepSeek, Mistral, GPT, and Llama. Each code sample also had an objective evaluation score. I was pleasantly surprised to see so many solutions for the same problem. I picked gpt-oss-20b model from OpenAI. For this experiment, I wanted to focus on learning how to code better so either one of the LLMs could have worked. But VibeCodeArena can also be used to evaluate different LLMs to help make a decision about which model to use for what problem statement.

The model had produced a clean HTML, CSS, and JavaScript. The code looked professional. I could see the preview of the code by clicking on the render icon. It worked perfectly in my browser. The carousel was smooth, and the images loaded beautifully.

But was it actually good code?

I had no idea. That's when I decided to look at the evaluation metrics

What I Thought Was "Good Code"

A working image carousel with:

  • Clean, semantic HTML
  • Smooth CSS transitions
  • Keyboard navigation support
  • ARIA labels for accessibility
  • Error handling for failed images

It looked like something a senior developer would write. But I had questions:

Was it secure? Was it optimized? Would it scale? Were there better ways to structure it?

Without objective evaluation, I had no answers. So, I proceeded to look at the detailed evaluation metrics for this code

What VibeCodeArena's Evaluation Showed

The platform's objective evaluation revealed issues I never would have spotted:

Security Vulnerabilities (The Scary Ones)

No Content Security Policy (CSP): My carousel was wide open to XSS attacks. Anyone could inject malicious scripts through the image URLs or manipulate the DOM. VibeCodeArena flagged this immediately and recommended implementing CSP headers.

Missing Input Validation: The platform pointed out that while the code handles image errors, it doesn't validate or sanitize the image sources. A malicious actor could potentially exploit this.

Hardcoded Configuration: Image URLs and settings were hardcoded directly in the code. The platform recommended using environment variables instead - a best practice I completely overlooked.

SQL Injection Vulnerability Patterns: Even though this carousel doesn't use a database, the platform flagged coding patterns that could lead to SQL injection in similar contexts. This kind of forward-thinking analysis helps prevent copy-paste security disasters.

Performance Problems (The Silent Killers)

DOM Structure Depth (15 levels): VibeCodeArena measured my DOM at 15 levels deep. I had no idea. This creates unnecessary rendering overhead that would get worse as the carousel scales.

Expensive DOM Queries: The JavaScript was repeatedly querying the DOM without caching results. Under load, this would create performance bottlenecks I'd never notice in local testing.

Missing Performance Optimizations: The platform provided a checklist of optimizations I didn't even know existed:

  • No DNS-prefetch hints for external image domains
  • Missing width/height attributes causing layout shift
  • No preload directives for critical resources
  • Missing CSS containment properties
  • No will-change property for animated elements

Each of these seems minor, but together they compound into a poor user experience.

Code Quality Issues (The Technical Debt)

High Nesting Depth (4 levels): My JavaScript had logic nested 4 levels deep. VibeCodeArena flagged this as a maintainability concern and suggested flattening the logic.

Overly Specific CSS Selectors (depth: 9): My CSS had selectors 9 levels deep, making it brittle and hard to refactor. I thought I was being thorough; I was actually creating maintenance nightmares.

Code Duplication (7.9%): The platform detected nearly 8% code duplication across files. That's technical debt accumulating from day one.

Moderate Maintainability Index (67.5): While not terrible, the platform showed there's significant room for improvement in code maintainability.

Missing Best Practices (The Professional Touches)

The platform also flagged missing elements that separate hobby projects from professional code:

  • No 'use strict' directive in JavaScript
  • Missing package.json for dependency management
  • No test files
  • Missing README documentation
  • No .gitignore or version control setup
  • Could use functional array methods for cleaner code
  • Missing CSS animations for enhanced UX

The "Aha" Moment

Here's what hit me: I had no framework for evaluating code quality beyond "does it work?"

The carousel functioned. It was accessible. It had error handling. But I couldn't tell you if it was secure, optimized, or maintainable.

VibeCodeArena gave me that framework. It didn't just point out problems, it taught me what production-ready code looks like.

My New Workflow: The Learning Loop

This is when I discovered the real power of the platform. Here's my process now:

Step 1: Generate Code Using VibeCodeArena

I start with a prompt and let the AI generate the initial solution. This gives me a working baseline.

Step 2: Analyze Across Several Metrics

I can get comprehensive analysis across:

  • Security vulnerabilities
  • Performance/Efficiency issues
  • Performance optimization opportunities
  • Code Quality improvements

This is where I learn. Each issue includes explanation of why it matters and how to fix it.

Step 3: Click "Challenge" and Improve

Here's the game-changer: I click the "Challenge" button and start fixing the issues based on the suggestions. This turns passive reading into active learning.

Do I implement CSP headers correctly? Does flattening the nested logic actually improve readability? What happens when I add dns-prefetch hints?

I can even use AI to help improve my code. For this action, I can use from a list of several available models that don't need to be the same one that generated the code. This helps me to explore which models are good at what kind of tasks.

For my experiment, I decided to work on two suggestions provided by VibeCodeArena by preloading critical CSS/JS resources with <link rel="preload"> for faster rendering in index.html and by adding explicit width and height attributes to images to prevent layout shift in index.html. The code editor gave me change summary before I submitted by code for evaluation.

Step 4: Submit for Evaluation

After making improvements, I submit my code for evaluation. Now I see:

  • What actually improved (and by how much)
  • What new issues I might have introduced
  • Where I still have room to grow

Step 5: Hey, I Can Beat AI

My changes helped improve the performance metric of this simple code from 82% to 83% - Yay! But this was just one small change. I now believe that by acting upon multiple suggestions, I can easily improve the quality of the code that I write versus just relying on prompts.

Each improvement can move me up the leaderboard. I'm not just learning in isolation—I'm seeing how my solutions compare to other developers and AI models.

So, this is the loop: Generate → Analyze → Challenge → Improve → Measure → Repeat.

Every iteration makes me better at both evaluating AI code and writing better prompts.

What This Means for Learning to Code with AI

This experience taught me three critical lessons:

1. Working ≠ Good Code

AI models are incredible at generating code that functions. But "it works" tells you nothing about security, performance, or maintainability.

The gap between "functional" and "production-ready" is where real learning happens. VibeCodeArena makes that gap visible and teachable.

2. Improvement Requires Measurement

I used to iterate on code blindly: "This seems better... I think?"

Now I know exactly what improved. When I flatten nested logic, I see the maintainability index go up. When I add CSP headers, I see security scores improve. When I optimize selectors, I see performance gains.

Measurement transforms vague improvement into concrete progress.

3. Competition Accelerates Learning

The leaderboard changed everything for me. I'm not just trying to write "good enough" code—I'm trying to climb past other developers and even beat the AI models.

This competitive element keeps me pushing to learn one more optimization, fix one more issue, implement one more best practice.

How the Platform Helps Me Become A Better Programmer

VibeCodeArena isn't just an evaluation tool—it's a structured learning environment. Here's what makes it effective:

Immediate Feedback: I see issues the moment I submit code, not weeks later in code review.

Contextual Education: Each issue comes with explanation and guidance. I learn why something matters, not just that it's wrong.

Iterative Improvement: The "Challenge" button transforms evaluation into action. I learn by doing, not just reading.

Measurable Progress: I can track my improvement over time—both in code quality scores and leaderboard position.

Comparative Learning: Seeing how my solutions stack up against others shows me what's possible and motivates me to reach higher.

What I've Learned So Far

Through this iterative process, I've gained practical knowledge I never would have developed just reading documentation:

  • How to implement Content Security Policy correctly
  • Why DOM depth matters for rendering performance
  • What CSS containment does and when to use it
  • How to structure code for better maintainability
  • Which performance optimizations actually make a difference

Each "Challenge" cycle teaches me something new. And because I'm measuring the impact, I know what actually works.

The Bottom Line

AI coding tools are incredible for generating starting points. But they don't produce high quality code and can't teach you what good code looks like or how to improve it.

VibeCodeArena bridges that gap by providing:

✓ Objective analysis that shows you what's actually wrong
✓ Educational feedback that explains why it matters
✓ A "Challenge" system that turns learning into action
✓ Measurable improvement tracking so you know what works
✓ Competitive motivation through leaderboards

My "simple image carousel" taught me an important lesson: The real skill isn't generating code with AI. It's knowing how to evaluate it, improve it, and learn from the process.

The future of AI-assisted development isn't just about prompting better. It's about developing the judgment to make AI-generated code production-ready. That requires structured learning, objective feedback, and iterative improvement. And that's exactly what VibeCodeArena delivers.

Here is a link to the code for the image carousal I used for my learning journey

#AIcoding #WebDevelopment #CodeQuality #VibeCoding #SoftwareEngineering #LearningToCode

Vibe Coding: Shaping the Future of Software

A New Era of Code Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change Discover how vibe coding is reshaping software development. Learn about its benefits, challenges, and what it means for developers in the AI era.
Author
Vishwastam Shukla
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November 8, 2025
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3 min read

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing c

Vibe Coding Difference

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable or Hostinger Horizons enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.​

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.​
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.​

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

How Candidates Use Technology to Cheat in Online Technical Assessments

Discover common technologies used by candidates for cheating in online assessments. Explore effective prevention methods like proctoring, AI monitoring, and smart test formats.
Author
Nischal V Chadaga
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December 1, 2025
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3 min read

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. At the same time, some organizations complement their process with context-aware code security support to ensure AI-generated solutions follow secure development practices. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

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Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.

Talent Acquisition Strategies For Rehiring Former Employees

Discover effective talent acquisition strategies for rehiring former employees. Learn how to attract, evaluate, and retain top boomerang talent to strengthen your workforce.
Author
Nischal V Chadaga
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November 8, 2025
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3 min read
Former employees who return to work with the same organisation are essential assets. In talent acquisition, such employees are also termed as ‘Boomerang employees’. Former employees are valuable because they require the least training and onboarding because of their familiarity with the organization’s policies. Rehiring former employees by offering them more perks is a mark of a successful hiring process. This article will elaborate on the talent acquisition strategies for rehiring former employees, supported by a few real-life examples and best practices.

Why Should Organizations Consider Rehiring?

One of the best ways of ensuring quality hire with a low candidate turnover is to deploy employee retention programs like rehiring female professionals who wish to return to work after a career break. This gives former employees a chance to prove their expertise while ensuring them the organization’s faith in their skills and abilities. Besides, seeing former employees return to their old organizations encourages newly appointed employees to be more productive and contribute to the overall success of the organization they are working for. A few other benefits of rehiring old employees are listed below.

Reduced Hiring Costs

Hiring new talent incurs a few additional costs. For example, tasks such as sourcing resumes of potential candidates, reaching out to them, conducting interviews and screenings costs money to the HR department. Hiring former employees cuts down these costs and aids a seamless transition process for them.

Faster Onboarding

Since boomerang employees are well acquainted with the company’s onboarding process, they don’t have to undergo the entire exercise. A quick, one-day session informing them of any recent changes in the company’s work policies is sufficient to onboard them.

Retention of Knowledge

As a former employee, rehired executives have knowledge of the previous workflows and insights from working on former projects. This can be valuable in optimizing a current project. They bring immense knowledge and experience with them which can be instrumental in driving new projects to success.Starbucks is a prime example of a company that has successfully leveraged boomerang employees. Howard Schultz, the company's CEO, left in 2000 but returned in 2008 during a critical time for the firm. His leadership was instrumental in revitalizing the brand amid financial challenges.

Best Practices for Rehiring Former Employees

Implementing best practices is the safest way to go about any operation. Hiring former employees can be a daunting task especially if it involves someone who was fired previously. It is important to draft certain policies around rehiring former employees. Here are a few of them that can help you to get started.

1. Create a Clear Rehire Policy

While considering rehiring a former employee, it is essential to go through data indicating the reason why they had to leave in the first place. Any offer being offered must supersede their previous offer while marking clear boundaries to maintain work ethics. Offer a fair compensation that justifies their skills and abilities which can be major contributors to the success of the organization. A well-defined policy not only streamlines the rehiring process but also promotes fairness within the organization.

2. Conduct Thorough Exit Interviews

Exit interviews provide valuable insights into why employees leave and can help maintain relationships for potential future rehires. Key aspects to cover include:
  • Reasons for departure.
  • Conditions under which they might consider returning.
  • Feedback on organizational practices.
Keeping lines of communication open during these discussions can foster goodwill and encourage former employees to consider returning when the time is right.

3. Maintain Connections with Alumni

Creating and maintaining an alumni association must be an integral part of HR strategies. This exercise ensures that the HR department can find former employees in times of dire need and indicates to former employees how the organization is vested in their lives even after they have left them. This gesture fosters a feeling of goodwill and gratitude among former hires. Alumni networks and social media groups help former employees stay in touch with each other, thus improving their interpersonal communication.Research indicates that about 15% of rehired employees return because they maintained connections with their former employers.

4. Assess Current Needs Before Reaching Out

Before reaching out to former employees, assess all viable options and list out the reasons why rehiring is inevitable. Consider:
  • Changes in job responsibilities since their departure.
  • Skills or experiences gained by other team members during their absence.
It is essential to understand how the presence of a boomerang employee can be instrumental in solving professional crises before contacting them. It is also important to consider their present circumstances.

5. Initiate an Honest Conversation

When you get in touch with a former employee, it is important to understand their perspective on the job being offered. Make them feel heard and empathize with any difficult situations they may have had to face during their time in the organization. Understand why they would consider rejoining the company. These steps indicate that you truly care about them and fosters a certain level of trust between them and the organization which can motivate them to rejoin with a positive attitude.

6. Implement a Reboarding Program

When a former employee rejoins, HR departments must ensure a robust reboarding exercise is conducted to update them about any changes within the organization regarding the work policies and culture changes, training them about any new tools or systems that were deployed during their absence and allowing them time to reconnect with old team members or acquaint with new ones.

7. Make Them Feel Welcome

Creating a welcoming environment is essential for helping returning employees adjust smoothly. Consider:
  • Organizing team lunches or social events during their first week.
  • Assigning a mentor or buddy from their previous team to help them reacclimate.
  • Providing resources that facilitate learning about any organizational changes.
A positive onboarding experience reinforces their decision to return and fosters loyalty.

Real-Life Examples of Successful Rehiring

Several companies have successfully implemented these strategies:

IBM: The tech giant has embraced boomerang hiring by actively reaching out to former employees who possess critical skills in emerging technologies. IBM has found that these individuals often bring fresh perspectives that contribute significantly to innovation7.

Zappos: Known for its strong company culture, Zappos maintains an alumni network that keeps former employees engaged with the brand. This connection has led to numerous successful rehiring instances, enhancing both morale and productivity within teams6.

Conclusion

Rehiring former employees can provide organizations with unique advantages, including reduced costs, quicker onboarding, and retained knowledge. By implementing strategic practices—such as creating clear policies, maintaining connections, assessing current needs, and fostering welcoming environments—companies can effectively tap into this valuable talent pool.

As organizations continue navigating an ever-changing workforce landscape, embracing boomerang employees may be key to building resilient teams equipped for future challenges. By recognizing the potential benefits and following best practices outlined above, businesses can create a robust strategy for rehiring that enhances both employee satisfaction and organizational performance.
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Senior vs Junior Developers Hiring Process - Comparison & Differences

A report on the National Employability of Engineers released last year by Aspiring Minds showed that a mere 3.67% of software engineers are employable for large-sized companies. Other statistics show that 90.72% of graduating engineers do not have the programming and algorithm skills desired by IT product companies, 72.77% lack soft-skills, and 59.40% lack cognitive skills.

With such dismal numbers, how do you test developers who are graduate or senior engineers with the right mix of skills to fulfill your requirements? In this article, we will talk about the hiring process for developers with the required talent for your company and what to focus on when hiring fresh and senior engineers.

Regardless of the level, you’re recruiting for, the first step is the same — defining your requirements in the form of skills needed and roles and responsibilities to be performed.

“Alice: Would you tell me, please, which way I ought to go from here?
The Cheshire Cat: That depends a good deal on where you want to get to.
Alice: I don’t much care where.
The Cheshire Cat: Then it doesn’t much matter which way you go.” – Lewis Carroll, Alice in Wonderland

Just like Alice, you will have trouble getting to your destination — finding the perfect candidates — if the path or requirements are not well-defined. Once you have defined the requirements, you can start the hiring process for your candidates.

Difference between senior and junior developers

Understanding the distinction between senior and junior developers is crucial for tailoring the hiring process effectively. These differences span various aspects, including:

Aspect
Junior Developers
Senior Developers
Experience and Skill Level
  • Less experience, often starting out or with a few years of professional experience.
  • Skills are foundational, focused on learning and growing within the role.
  • Extensive experience, often several years in the industry.
  • Advanced technical skills and deep understanding of programming languages, frameworks, and systems.
  • Capable of handling complex tasks with minimal supervision.
Problem-solving and Complexity
  • Developing problem-solving skills.
  • Suited for well-defined, less complex tasks.
  • Often require guidance to troubleshoot and solve problems.
  • Strong problem-solving skills, capable of tackling complex, ambiguous problems.
  • Can foresee potential issues and propose effective, scalable solutions.
Project Leadership and Mentoring
  • Not expected to lead projects or mentor others.
  • Focus on learning from others and gradually taking on more responsibility.
  • Often take on leadership roles within projects.
  • Mentor junior team members, provide guidance, and responsible for significant decision-making.
Autonomy and Decision Making
  • Require more oversight and direction.
  • Work often needs to be reviewed and validated by more experienced team members.
  • Operate with a high degree of autonomy.
  • Trusted to make critical decisions and often responsible for significant portions of a project or entire projects.
Contribution to Strategy and Planning
  • Focus on task execution, not heavily involved in strategic planning or high-level decision-making.
  • Play a key role in strategy, planning, and shaping the direction of projects.
  • Contribute to the broader technical strategy of the team or organization.
Salary and Investment
  • Command lower salaries, represent an investment in potential and growth within the company.
  • Have higher salary expectations, reflecting their experience and value in terms of expertise and leadership.
Cultural and Team Dynamics
  • Often bring fresh perspectives and new energy to a team, beneficial for team dynamics and innovation.
  • Experience significantly influences team culture and dynamics.
  • Often set technical standards and best practices within the team.

Hiring Process for a Fresh Graduate

Since a degree is clearly not a relevant measure of employability, it is critical that the hiring process is able to ascertain in other ways whether the candidate has the right skills and is a good fit for the company. It should check whether the candidate has technical acumen along with necessary soft skills such as the communication and interpersonal skills to work in a team. The hiring process for a fresh engineer looks something like this:

Sourcing

The first step in the hiring process is to source the right candidates for the job. You could try campus placements, use outside recruiters who do the sourcing for you or use inbound recruitment techniques to attract the right candidates. Any or all of these sources could give you a pool of candidates for consideration.

in this FastCompany article, Keawe Block, a recruiter at Google, says that they look for candidates who have experience at hackathons, coding competitions, or have had programming assignments at work. Check the resumes to see what coding languages they know, and what relevant internships they might have done. These give an insight into their technical acumen which can be tested further in the next stages.

Screening

You have a targeted pool of potential recruits. The next step is to filter them further by testing these candidates on their technical skills. Alternatively, you can use tools (such as HackerEarth Recruit) which have an online coding test, that allows you to check scores in real-time and use detailed test reports to analyze performance.

Selection

Depending on the job requirement, this could be an interview or a series of interviews with supervisors and peers. If your engineers are expected to work in an agile environment, your questions should check for whether the candidate is a team player, is patient, and resilient as she would be working for long periods of time with the rest of the team. Check mainly for “fit,” whether you see the person blending in and growing with the company.

Lastly, it does not matter if the candidate is not a full-stack developer, as long as she demonstrates a willingness to learn and has the right attitude. Technical requirements of companies are ever-changing, and any skills one has today might be rendered redundant tomorrow.

On-Demand Webinar

Hiring Process for a Senior Developer

The hiring process for a senior developer differs vastly from that of a fresh graduate. For starters, the emphasis is on experience and accomplishments in past roles. The other vital difference is in sourcing senior managers, which is much more challenging because of the limited pool of qualified senior engineers available.

The hiring process for a senior developer looks something like this:

Sourcing

With fresh engineers, there is a problem of plenty; with senior engineers, the opposite holds true. There are few engineers at the senior level who have skills that you need, and they might not be motivated to switch jobs. Referrals are the perhaps the best approach to attract candidates in this case as they referrals a mutual interest from both the employer and the potential hire. You can also use inbound recruitment techniques, such as your website and social media handles, to advertise and invite candidates to apply. Alternatively, you can use recruiters to do the sourcing for you.

Screening

The quickest way to screen candidates is to conduct telephonic interviews where you can ask them for further details about their experience and skills. A more detailed way to check their acumen would be to assign a coding test, allocate some time to work on it and do a review with them. This gives you a chance to see them in action and judge their ability in a practical manner.

Selection

The selection involves interviews with the top management. The number of interviews is usually lesser for a senior engineer than a fresh graduate. The interview will focus on the candidate’s experience and how that might be relevant to the role that the candidate is being interviewed for. The interview should focus on how he has demonstrated leadership skills in the past with relevant examples. A candidate that attends conferences and technology meet-ups indicates that she’s in touch with changing technology trends.

No One-Size-Fits-all-Solution

Since the requirements for graduates and senior engineers are different, the skills tested and the hiring process cannot be the same for both. While you look for leadership skills, stability, and relevant experience for a senior engineer; you look for aptitude, a willingness to learn, and culture fit while hiring fresh engineers. As stated above, it all needs to tie back to the company’s requirements. A vital point of difference is also negotiations with senior candidates. It is difficult to make the switch if they don’t get the salary they’re looking for. With fresh graduates, because of the abundant supply, it is possible to find someone in your budget, but with senior engineers, the salary must be lucrative enough, hence the negotiations take longer.

If you are looking for a recruitment solution to efficiently hire fresh and senior talent for your organization, sign up for a free trial of HackerEarth Recruit

Top women programmers in history

It's a common notion that technology is a field dominated by men, but the truth is that technology and programming are not bound by gender—they're for everyone. A quick look online reveals countless women who have made remarkable contributions to the field of technology.

Here are some inspiring women who have made it big in tech:

1) Ada Lovelace (1815 – 1852)

Ada Lovelace, born in 1815 in London, is considered a pioneer of programming. She is best known for her work interpreting Charles Babbage's analytical engine, a foundational concept in the evolution of computers. The Ada programming language was named in her honor.

Ada Lovelace

2) Grace Hopper (1906 – 1992)

Grace Hopper was a trailblazing computer scientist and US Navy officer. She developed the first compiler for a programming language and played a key role in creating COBOL, one of the first high-level programming languages.

Grace Hopper

3) The ENIAC Programmers

Six women—Kathleen McNulty, Jean Jennings, Frances Snyder, Marlyn Meltzer, Frances Spence, and Ruth Teitelbaum—were the first programmers of the fully electronic ENIAC computer. Despite their groundbreaking work, they initially received little credit.

ENIAC Programmers

4) Edith Clarke (1883 – 1959)

The first female electrical engineer and professor of electrical engineering at the University of Texas at Austin. She developed the Clarke calculator, which solved complex equations involving hyperbolic functions significantly faster than previous methods.

Edith Clarke

5) Evelyn Boyd Granville (1924 – )

One of the first African-American women to earn a Ph.D. in mathematics. She contributed to NASA’s space missions by computing rocket trajectories and orbit paths, later becoming a dedicated educator and advocate for women in tech.

Evelyn Boyd Granville

6) Sister Mary Kenneth Keller (1913 – 1985)

Among the first Americans to receive a Ph.D. in computer science. She worked on the BASIC programming language and helped found the computer science department at Clarke College to promote accessible tech education.

Sister Mary Kenneth Keller

7) Carol Shaw (1955 – )

Regarded as the first female video game designer. She created popular games like River Raid and 3-D Tic-Tac-Toe for Atari Inc., shaping the early days of video gaming.

Carol Shaw

8) Janese Swanson (1958 – )

Founder of Girl Tech, a company that aims to make technology more accessible and appealing to girls. She started her career in tech sales, later earning advanced degrees before launching Girl Tech to support girls in STEM.

Janese Swanson

9) Radia Perlman (1958 – )

Known as the "Mother of the Internet," Radia invented the Spanning-Tree Protocol (STP), a critical part of network infrastructure. She holds over 100 patents and made significant contributions to routing and network protocols.

Radia Perlman

10) Parisa Tabriz (1983 – )

Known as Google's "Security Princess," Parisa leads global security for Google Chrome. Inspired by her own website being hacked in college, she now works on cybersecurity, advocating for safer, privacy-respecting internet technologies. In today’s era of connected devices from smartphones to smart TVs her efforts remind us of the importance of securing our digital lives, whether it's browsing safely or using a VPN for smart TV to protect streaming data from prying eyes.

Parisa Tabriz

“There is no demand for women engineers, as such, as there are for women doctors; but there is always a demand for anyone who can do a good piece of work.” – Edith Clarke

These remarkable women show that determination, intelligence, and innovation transcend gender. Their stories continue to inspire a new generation of engineers, coders, and creators.

Key Secret to a Successful Software Development Internship

Internships in software development are good for both the company and the interns. As a developer, internship projects teach you how to build a successful software product. For a company, interns bring in the diversity and fresh perspectives that are required to take the product to the next level.

But what makes an internship in software development successful? Here are 7 strong signs that tell you whether the 2-6 months you spent during your internship were worthwhile.

1) If you improved your technical skills

At college, you are exposed to various technical concepts. An internship gives hands-on exposure to technical concepts that you learned at school. You can code and build software, from scratch. If you feel your internship has helped improve your technical skills, consider it a job well done.

2) If you learned how to build a product

The best part about interning in a software development team is the opportunity to learn how to build a successful software product. As part of the product team, you interact with stakeholders from different teams and levels of management. You gain a better understanding of the end-user, the business objectives, and the role of software in attaining those goals. Rather than working in isolation, you are part of a team with people from various domains with different levels of experience. This exposure teaches you to manage time and build software per the expectation of stakeholders. If at the end of your internship, you have learned how to build a product, consider it a job well done.

3) If you’ve enhanced your soft skills

Internships are not only about enhancing technical skills, but also about acquiring interpersonal skills. As an intern, you can make friends and network with new people at work. The ability to work in a team with different people is crucial for a successful career in software development. Interning in a software development team also makes you better at presenting ideas clearly. If your internship has made you a better communicator, consider it a job well done.

4) If you've learned something new

Usually, interns are taken based on the merit of what they can do. Interns are tested for their technical skills or are taken based on the merit of their past work. Apart from the project they are assigned to, interns also get exposure to a lot of business operations. This adds a lot of value to one’s professional profile.

At the end of your internship, if you get the "bigger picture," consider it a job well done.

5) When you've built something of lasting impact

In a recent tech event, Max Levchin, one of the founders of PayPal, shared a story of an intern who saved the company from going bust. It was the early 2000s and credit card fraud was hurting PayPal big time. The intern's job was to build an anti-theft system called IGOR that eventually saved the company. The intern died soon after due to a diabetes complication, and Levchin said PayPal may not exist today without him. Not every contribution can be as significant, but the point is that if you know that you've built something of value and can see how it fits in the bigger scheme of things, it's a job well done.

6) If you figured out what you don't want to do

In college, you often want to do something, but you have no idea what or how. An internship is the best way to find out if your dream job is everything that you thought it would be. Often, it is not going to be what you think it is and that's perfectly alright. It will be one less thing on your list when you're trying to figure out what you want to do with your life. You might be really good at what you do too, but if you're not enjoying it, it's not worth pursuing all your life.

Finding out what you don't want to do is just as important as finding out what you love to do. If you come across the former, consider your internship a job well done.

7) If at the end of the internship, you didn't want to leave, and the company also didn't want to let you go

*Sniff*

Congratulations on the full-time offer! Job well done.

Additional tip to rock your internship

Don’t go after money. The second you make your internship decision on the basis of money, 99% of the time, you would have made a compromise. There would be that job which sounded like something right up your alley, but you didn't take it, because there was this other, probably more boring job, which paid more.

Try not to do that. If you didn't, it's already a job well done.

Internship at HackerEarth

At HackerEarth, we have a strong support system for interns. We have an open and collaborative work culture. Our full-time software engineers and product managers are always available to help and mentor new interns. View current internship opportunities here: https://www.hackerearth.com/companies/hackerearth/jobs/

How can mathematics make you a better recruiter!

Hiring the right talent is crucial to any organization’s growth and success. “By implementing recruiting best practices and supporting technology, you can potentially reduce your time to hire by up to 50 percent, reduce cost per hire by up to 70 percent, and improve recruiter efficiency while finding the talent you need for driving business results.”1

Companies try everything from recruiting agencies to job boards to employee referrals to social media. But the efficacy of these approaches can be often debatable. But that’s a post for another day.

Here, we bring you some sure-fire concepts that will boost hiring efficiency.

Did you say mathematics?

Yes, you read it right. Mathematics! Perhaps the most hated subject ever, math can help recruiters solve one of the most prominent problems they face while trying to zero in on great talent.

Let’s see how exactly it helps.

How many candidates should you interview before making a decision to hire? Imagine a situation where you have a hundred applicants for a position. The problem is that neither will you interview just one candidate nor will you interview all hundred. The dilemma is not whom to pick but how many to even consider before you hire (or you give up).

The most intuitive answer would be that it requires a balance between looking and leaping - that you must look at enough candidates to build a standard and decide on whatever satisfies the established standard. This looks like the perfect answer but here is the catch. Most people can’t say what this standard or balance should be. Luckily, mathematics comes to your rescue and provides the answer. Optimal Stopping Theory...

It is an idea “that every decision is a decision to stop what you are going to make a decision.”2 The theory suggests that you should reject the initial 37% of all the applicants and hire only after that. After this point, you should select the next applicant who is better than all candidates you interviewed before the cutoff. This is not intuition or a compromise between looking and leaping. It is a probable result.



Here look at this example if you have five weeks to choose a primary contractor. You could expect to see possibly four a week; that is an anticipated total of 20 suppliers. If you selected normally and selected the first ‘good enough’ option, the probability of finding the optimum supplier is just 5%. However, if you rejected the first 37% suppliers, in this case, 18 suppliers, and then selected the next supplier that was better than all the previous suppliers, then your odds of selecting the optimum supplier would increase to 40% (For the more curious people, go here to read about the famous example, the Secretary problem.)

This is just one of the mathematical theories that can help recruiters. To list a few more, there is Negativity Threshold which can help you identify the candidates that are inconsistent in their interview answers or are withholding information. Negativity Threshold was presented by Hannah Fry in her TED talk “The Mathematics of Love.” It was coined by John Gottman by observing how couples interact with each other.

The equations look something like this:

Mathematics, Recruiter, Mathematics in hiring, mathematics example, Recruitment, Hiring, Mathematics in recruitment

The left-hand side of the equation tells how positive or negative a wife/husband will be in the next thing she/he says. Here, w is the mood of the wife in general, r_w.W_t is the mood of the wife when she’s with her husband and I_(HM) is the influence that her husband’s actions will have on her. Researchers have plotted the effects the two partners have on each other. The plot looks as follows:

Mathematics, Recruiter, Mathematics in hiring, mathematics example, Recruitment, Hiring, Mathematics in recruitment

Here, the term T_ is the negativity threshold. At this point, the husband’s negative impact becomes so high that the wife responds with more negativity. To know more about this theory you can watch [ted talk link] or read this.

The negativity threshold suggests you be upfront about any issues and get all sorts of concerns out in open to avoid issues further down the line.

Another interesting equation that is worth looking at is The Drake Equation. The equation was conceived in 1961 by Dr. Frank Drake in an attempt to find the number of potential extraterrestrial bodies with life in the universe. He took something extremely complex and daunting and broke it down into something easy to understand. The Drake equation looks something like this:
N = R*•fp• ne• fl• fi• fc• L

The equation involves various factors such as the average rate of star formation in our galaxy, the fraction of stars that have formed planets, and much more which we will not get into. But, what how does this apply to hiring practices? A very obvious similarity is that both use data to pinpoint something or “someone” out there.

An important step in hiring candidates is determining the business factors your company wants to improve, says Emilio J. Castilla, Nanyang Technological University professor of management at the MIT Sloan School of Management. Determining these factors brings clarity to the business and helps everyone understand their roles. For instance, there is something called Sales Velocity, defined as:
Sales Velocity = Work In Progress ? Win Rate ? Avg. Deal Size ÷ Time Taken To Close

This equation does not help in identifying the top performers but also helps in determining the areas where an individual needs to improve. Drake’s theory is extremely useful when it comes to bringing order to a chaotic world.

Although most of the recruiting process is often dominated by emotion, mathematics is the one subject which can be applied everywhere, even hiring, without this particular bias.

Can you math enthusiasts think of any more? Let us know in Comments.

& for some of you who are super busy or are less inclined to "appreciating" math concepts, let us do the work for you.

Take a free trial for our Online Assessment software to hire the best mathematician (or developers) in your talent pipeline

Artificial Intelligence 101: How to get started

What is Artificial Intelligence (AI)?

Are you thinking of Chappie, Terminator, or Lucy? Sentient, self-aware robots are closer to becoming a reality than you might think. AI focuses on developing software or machines that exhibit human-like intelligence. Simply put, AI is the study of computer science aimed at creating intelligent systems.

Of course, there’s more to it. AI spans a range of applications—from simple calculators to self-steering technology, with the potential to radically transform the future.

Goals and Applications of AI

Machine learning challenge, ML challenge

AI aims to enable machines to reason, represent knowledge, plan, process natural language, learn, perceive, and manipulate objects. Long-term goals include creativity, social intelligence, and achieving general (human-level) intelligence.

AI is embedded deeply in every industry. Ray Kurzweil notes that thousands of AI applications are part of our global infrastructure. John McCarthy, one of AI’s founders, remarked, “as soon as it works, no one calls it AI anymore.” According to recent statistics, the global AI market is expected to reach $305.9 billion by 2024.

AI Types Chart

Source: Bluenotes

Types of AI

AI can be categorized based on its capabilities:

Weak AI (Narrow AI): Focuses on specific tasks with no self-awareness. Example: Siri, which combines multiple weak AI techniques to function.

Strong AI (True AI): Exhibits human-level intelligence, capable of performing any intellectual task a human can do. This includes fictional examples like Matrix or I, Robot.

Artificial Superintelligence: Described by Nick Bostrom as “an intellect that is much smarter than the best human brains in practically every field.” This is the type of AI that raises ethical and existential concerns among experts like Stephen Hawking and Elon Musk.

How Can You Get Started?

Start by learning a programming language—Python is recommended due to its machine learning libraries.

Here are some Python learning resources:

Introduction to Bots

A bot is a simple form of weak AI designed to automate tasks. Examples include chatbots and web crawlers.

Before building bots, it’s useful to learn:

  • XPath – for inspecting and targeting HTML
  • Regex – for data processing and pattern matching
  • REST – for working with APIs

How Can You Build Your First Bot?

Start with simple Python tutorials:

Use APIs to develop user applications quickly:

Practice with these bot-building challenges:

What Now?

Once comfortable with a programming language, dive into machine learning. In Python, explore libraries such as Scikit-learn, NLTK, SciPy, PyBrain, and NumPy. Knowledge of advanced math will also be essential. AI-powered tools can even help you learn math effectively, like those listed here.

Here are more resources to learn and practice:

Additional Reading:

Participate in AI & Bot Contests:

Ready to dive deeper? Learn how AI is changing the world.

Popular posts like this:

  1. How to Hire a Data Scientist
  2. 5 Must-Have Proctoring Tips
  3. How to Prevent Tech Talent Poaching

Highlights of IndiaHacks 2017

Innovation was the focal point of IndiaHacks 2017, the fourth edition of HackerEarth’s country-wide event, conducted in partnership with IBM and Honeywell. The two-day event dedicated to programming was conducted on the 8th and 9th of September 2017 in Bangalore.The two-day event included a hackathon, two online programming challenges, and a tech conference. The event had over 55,000+ registrations with tech talks from some of the most prominent leaders in the IT sector.

Highlights from IndiaHacks 2017
Highlights of IndiaHacks 2017

The best hacks of the event

45 teams of programmers, designers, and project managers came together to build epic products at the offline hackathon event which had 3 main tracks – Internet of Things, Fintech, and AI. Submissions were received in areas including smart wearables, smart medical devices, smart driving experience, financial advisory, security, personal finance, blockchain, document life cycle management, recommendation systems, chatbots, and language processing systems.

Here are some of the best hacks of the event:

1) License integrated safety device

The license integrated safety device is a UUID-based vehicle tracking system which addresses the growing need for delivering effective safety, traffic control, and pollution control on roads. The technology can serve as a first responder management service in smart cities.

2) Real-time assistant for badminton players

The real-time assistant is a wearable device that enables players to know their fitness level, and match readiness by analyzing their “smash” profile. This profile has fitness details such as calorie intake, fluid intake, workout before sessions, and performance levels.

3) GPS- and IoT-based soldier tracking and health indication system

The low cost, IoT-based wearable device is equipped with biosensors. The device offers a reliable system to guard the lives of soldiers. The system can help locate and monitor the health of soldiers in combat.

4) TechnoFin: a simpler solution for managing financial problems

With time-series modelling and predictive analysis, TechnoFin serves as a full-fledged financial recommendation engine. It addresses all the problems related to investing in stock market, real-estate, gold, and banking.

5) Money multiplier

Money multiplier, an app integrated with Watson Conversation, aims to educate the financially illiterate. The app helps in the analysis of monthly account statements, monthly limit for savings, and helps users understand the Net Asset Value(NAV) of mutual funds.

6) Security for financial transactions

The ML-based security software aims to make transactions safer by identifying and tracking user behavior. Using Apache Lucene-based Elastic search or Solr engine, the software stores transactional data and identifies user pattern.

7) Smart Courses

The smart online learning software uses an image recognition recommendation system to evaluate facial expressions of students and operates accordingly. The system can be equipped with a smart assistant or chatbot to answer user queries.

8) Genre-switching music recommendation system

The recommendation software specializes in giving a good mix of genres based on the correlation established between the tapped genres using reinforcement learning.

9) Bot104

BOT 104 tracks the number of beds available in nearby hospitals and allows users to book hospital beds easily. The software also has a feature to auto-generate bills using custom QR codes.

IndiaHacks Tech Conference 2017

The IndiaHacks tech conference had many insightful sessions by some amazing tech leaders. The conference had 9 tech talks, 2 panel discussions, and 16 tech huddles on topics related to various tech domains like machine learning , artificial intelligence, APIs, and cloud computing. Speakers from IBM, ThoughtWorks, Honeywell, RBS, Credit Suisse, and other sponsoring companies shared their insights on various topics such as blockchain, chatbots, big data, and fintech.

IndiaHacks Conference 2017
IndiaHacks Conference 2017

With the increasing dominance of technology in every aspect of our life from banking to healthcare, there is greater pressure on software makers to meet commercial and consumer expectations. The tech conference featured discussions on industry trends, research, and latest innovation to build and maintain revolutionary, scalable software. The event also had an exhibition area, where sponsoring companies showcased their latest software products and services. The exhibition area was abuzz with interactive activities that included insightful demos, creative games, and contests.

https://twitter.com/TharikaTelliche/status/906860304184651776

With an outreach of over 2 Million, IndiaHacks 2017 was one of biggest nationwide tech events of the year. The event provided a platform for industry leaders, investors, and some of the most talented programmers of the country to come together, and share their knowledge to tackle some of the biggest challenges in the software industry.

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AI In Recruitment: The Good, The Bad, The Ugly

Artificial Intelligence (AI) has permeated virtually every industry, transforming operations and interactions. The tech recruitment sector is no exception, and AI’s influence shapes the hiring processes in revolutionary ways. From leveraging AI-powered chatbots for preliminary candidate screenings to deploying machine learning algorithms for efficient resume parsing, AI leaves an indelible mark on tech hiring practices.

Yet, amidst these promising advancements, we must acknowledge the other side of the coin: AI’s potential malpractices, including the likelihood of cheating on assessments, issues around data privacy, and the risk of bias against minority groups.

The dark side of AI in tech recruitment

Negative impact of AI

The introduction of AI in recruitment, while presenting significant opportunities, also brings with it certain drawbacks and vulnerabilities. Sophisticated technologies could enable candidates to cheat on assessments, misrepresent abilities and potential hiring mistakes. This could lead to hiring candidates with falsifying skills or qualifications, which can cause a series of negative effects like:

  • Reduced work quality: The work output might be sub-par if a candidate doesn’t genuinely possess the abilities they claimed to have.
  • Team disruptions: Other team members may have to pick up the slack, leading to resentment and decreased morale.
  • Rehiring costs: You might have to let go of such hires, resulting in additional costs for replacement.

Data privacy is another critical concern

Your company could be left exposed to significant risks if your AI recruiting software is not robust enough to protect sensitive employee information. The implications for an organization with insufficient data security could be severe such as:

  • Reputational damage: Breaches of sensitive employee data can damage your company’s reputation, making it harder to attract clients and talented employees in the future.
  • Legal consequences: Depending on the jurisdiction, you could face legal penalties, including hefty fines, for failing to protect sensitive data adequately.
  • Loss of trust: A data breach could undermine employee trust in your organization, leading to decreased morale and productivity.
  • Financial costs: Besides potential legal penalties, companies could also face direct financial losses from a data breach, including the costs of investigation, recovery, and measures to prevent future breaches.
  • Operational disruption: Depending on the extent of the breach, normal business operations could be disrupted, causing additional financial losses and damage to the organization’s reputation.

Let’s talk about the potential for bias in AI recruiting software

Perhaps the most critical issue of all is the potential for unconscious bias. The potential for bias in AI recruiting software stems from the fact that these systems learn from the data they are trained on. If the training data contains biases – for example, if it reflects a history of preferentially hiring individuals of a certain age, gender, or ethnicity – the AI system can learn and replicate these biases.

Even with unbiased data, if the AI’s algorithms are not designed to account for bias, they can inadvertently create it. For instance, a hiring algorithm that prioritizes candidates with more years of experience may inadvertently discriminate against younger candidates or those who have taken career breaks, such as for child-rearing or health reasons.

This replication and possible amplification of human prejudices can result in discriminatory hiring practices. If your organization’s AI-enabled hiring system is found to be biased, you could face legal action, fines, and penalties. Diversity is proven to enhance creativity, problem-solving, and decision-making. In contrast, bias in hiring can lead to a homogenous workforce, so its absence would likely result in a less innovative and less competitive organization.

Also read: What We Learnt From Target’s Diversity And Inclusion Strategy

When used correctly, AI in recruitment can take your hiring to the next level

How to use AI during hiring freeze

How do you evaluate the appropriateness of using AI in hiring for your organization? Here are some strategies for navigating the AI revolution in HR. These steps include building support for AI adoption, identifying HR functions that can be integrated with AI, avoiding potential pitfalls of AI use in HR, collaborating with IT leaders, and so on.

Despite certain challenges, AI can significantly enhance tech recruitment processes when used effectively. AI-based recruitment tools can automate many manual recruiting tasks, such as resume screening and interview scheduling, freeing up time for recruiters to focus on more complex tasks. Furthermore, AI can improve the candidate’s experience by providing quick responses and personalized communications. The outcome is a more efficient, candidate-friendly process, which could lead to higher-quality hires.

Let’s look at several transformational possibilities chatbots can bring to human capital management for candidates and hiring teams. This includes automation and simplifying various tasks across domains such as recruiting, onboarding, core HR, absence management, benefits, performance management, and employee self-service resulting in the following:

For recruiters:

  • Improved efficiency and productivity: Chatbots can handle routine tasks like responding to common inquiries or arranging interviews. Thereby, providing you with more time to concentrate on tasks of strategic importance.
  • Enhanced candidate experience: With their ability to provide immediate responses, chatbots can make the application process more engaging and user-friendly.
  • Data and insights: Chatbots can collect and analyze data from your interactions with candidates. And provide valuable insights into candidate preferences and behavior.
  • Improved compliance: By consistently following predefined rules and guidelines, chatbots can help ensure that hiring processes are fair and compliant with relevant laws and regulations.
  • Cost saving: By automating routine tasks for recruiters, chatbots can help reduce the labor costs associated with hiring.

Also read: 5 Steps To Create A Remote-First Candidate Experience In Recruitment

How FaceCode Can Help Improve Your Candidate Experience | AI in recruitment

For candidates:

Additionally, candidates can leverage these AI-powered chatbots in a dialog flow manner to carry out various tasks. These tasks include the following:

  • Personalized greetings: By using a candidate’s name and other personal information, chatbots can create a friendly, personalized experience.
  • Job search: They can help candidates search for jobs based on specific criteria.
  • Create a candidate profile: These AI-powered chatbots can guide candidates through the process of creating a profile. Thus, making it easier for them to apply for jobs.
  • Upload resume: Chatbots can instruct candidates on uploading their resume, eliminating potential confusion.
  • Apply for a job: They can streamline the application process, making it easier and faster for candidates to apply for jobs.
  • Check application status: Chatbots can provide real-time updates on a candidate’s application status.
  • Schedule interviews: They can match candidate and interviewer availability to schedule interviews, simplifying the process.

For hiring managers:

These can also be utilized by your tech hiring teams for various purposes, such as:

  • Create requisition: Chatbots can guide hiring managers through the process of creating a job requisition.
  • Create offers: They can assist in generating job offers, ensuring all necessary information is included.
  • Access requisition and offers: Using chatbots can provide hiring managers with easy access to job requisitions and offers.
  • Check on onboarding tasks: Chatbots can help track onboarding tasks, ensuring nothing is missed.

Other AI recruiting technologies can also enhance the hiring process for candidates and hiring teams in the following ways:

For candidates:

  1. Tailor-made resumes and cover letters using generative AI: Generative AI can help candidates create custom resumes and cover letters, increasing their chances of standing out.
  2. Simplifying the application process: AI-powered recruiting tools can simplify the application process, allowing candidates to apply for jobs with just a few clicks.
  3. Provide similar job recommendations: AI can analyze candidates’ skills, experiences, and preferences to recommend similar jobs they might be interested in.

For recruiters:

  • Find the best candidate: AI algorithms can analyze large amounts of data to help you identify the candidates most likely to succeed in a given role.
  • Extract key skills from candidate job applications: Save a significant amount of time and effort by using AI-based recruiting software to quickly analyze job applications to identify key skills, thereby, speeding up the screening process.
  • Take feedback from rejected candidates & share similar job recommendations: AI can collect feedback from rejected candidates for you to improve future hiring processes and recommend other suitable roles to the candidate.

These enhancements not only streamline the hiring process but also improve the quality of hires, reduce hiring biases, and improve the experience for everyone involved. The use of AI in hiring can indeed take it to the next level.

Where is AI in recruitment headed?

AI can dramatically reshape the recruitment landscape with the following key advancements:

1. Blockchain-based background verification:

Blockchain technology, renowned for its secure, transparent, and immutable nature, can revolutionize background checks. This process which can take anywhere from between a day to several weeks today for a single recruiter to do can be completed within a few clicks resulting in:

  • Streamlined screening process: Blockchain can store, manage, and share candidates’ credentials and work histories. Thereby speeding up the verification and screening process. This approach eliminates the need for manual background checks. And leads to freeing up a good amount of time for you to focus on more important tasks.
  • Enhanced trust and transparency: With blockchain, candidates, and employers can trust the validity of the information shared due to the nature of the technology. The cryptographic protection of blockchain ensures the data is tamper-proof, and decentralization provides transparency.
  • Improved data accuracy and reliability: Since the blockchain ledger is immutable, it enhances the accuracy and reliability of the data stored. This can minimize the risks associated with false information on candidates’ resumes.
  • Faster onboarding: A swift and reliable verification process means candidates can be onboarded more quickly. Thereby, improving the candidate experience and reducing the time-to-hire.
  • Expanded talent pool: With blockchain, it’s easier and quicker to verify the credentials of candidates globally, thereby widening the potential talent pool.

2. Immersive experiences using virtual reality (VR):

VR can provide immersive experiences that enhance various aspects of the tech recruitment process:

  • Interactive job previews: VR can allow potential candidates to virtually “experience” a day i.e., life at your company. This provides a more accurate and engaging job preview than traditional job descriptions.
  • Virtual interviews and assessments: You can use VR to conduct virtual interviews or assessments. You can also evaluate candidates in a more interactive and immersive setting. This can be particularly useful for roles that require specific spatial or technical skills.
  • Virtual onboarding programs: New hires can take a virtual tour of the office, meet their colleagues, and get acquainted with their tasks, all before their first day. This can significantly enhance the onboarding experience and help new hires feel more prepared.
  • Immersive learning experiences: VR can provide realistic, immersive learning experiences for job-specific training or to enhance soft skills. These could be used during the recruitment process or for ongoing employee development.

Also read: 6 Strategies To Enhance Candidate Engagement In Tech Hiring (+ 3 Unique Examples)

AI + Recruiters: It’s all about the balance!

To summarize, AI in recruitment is a double-edged sword, carrying both promise and potential problems. The key lies in how recruiters use this technology, leveraging its benefits while vigilantly managing its risks. AI isn’t likely to replace recruiters or HR teams in the near future. Instead, you should leverage this tool to positively impact the entire hiring lifecycle.

With the right balance and careful management, AI can streamline hiring processes. It can create better candidate experiences, and ultimately lead to better recruitment decisions. Recruiters should continually experiment with and explore generative AI. To devise creative solutions, resulting in more successful hiring and the perfect fit for every open role.

Looking For A Mettl Alternative? Let’s Talk About HackerEarth

“Every hire is an investment for a company. A good hire will give you a higher ROI; if it is a bad hire, it will cost you a lot of time and money.”

Especially in tech hiring!

An effective tech recruitment process helps you attract the best talents, reduce hiring costs, and enhance company culture and reputation.

Businesses increasingly depend on technical knowledge to compete in today’s fast-paced, technologically driven world. Online platforms that provide technical recruiting solutions have popped up to assist companies in finding and employing top talent in response to this demand.

The two most well-known platforms in this field are HackerEarth and Mettl. To help businesses make wise choices for their technical employment requirements, we will compare these two platforms’ features, benefits, and limitations in this article.

This comparison of Mettl alternative, HackerEarth and Mettl itself, will offer helpful information to help you make the best decision, whether you’re a small company trying to expand your tech staff or a massive organization needing a simplified recruiting process.

HackerEarth

HackerEarth is based in San Francisco, USA, and offers enterprise software to aid companies with technical recruitment. Its services include remote video interviewing and technical skill assessments that are commonly used by organizations.

HackerEarth also provides a platform for developers to participate in coding challenges and hackathons. In addition, it provides tools for technical hiring such as coding tests, online interviews, and applicant management features. The hiring solutions provided by HackerEarth aid companies assess potential employees’ technical aptitude and select the best applicants for their specialized positions.

Mettl

Mettl, on the other hand, offers a range of assessment solutions for various industries, including IT, banking, healthcare, and retail. It provides online tests for coding, linguistic ability, and cognitive skills. The tests offered by Mettl assist employers find the best applicants for open positions and make data-driven recruiting choices. Additionally, Mettl provides solutions for personnel management and staff training and development.

Why should you go for HackerEarth over Mercer Mettl?

Here's why HackerEarth is a great Mettl Alternative!

Because HackerEarth makes technical recruiting easy and fast, you must consider HackerEarth for technical competence evaluations and remote video interviews. It goes above and beyond to provide you with a full range of functions and guarantee the effectiveness of the questions in the database. Moreover, it is user-friendly and offers fantastic testing opportunities.

The coding assessments by HackerEarth guarantee the lowest time consumption and maximum efficiency. It provides a question bank of more than 17,000 coding-related questions and automated test development so that you can choose test questions as per the job role.

As a tech recruiter, you may need a clear understanding of a candidate’s skills. With HackerEarth’s code replay capability and insight-rich reporting on a developer’s performance, you can hire the right resource for your company.

Additionally, HackerEarth provides a more in-depth examination of your recruiting process so you can continuously enhance your coding exams and develop a hiring procedure that leads the industry.

HackerEarth and Mercer Mettl are the two well-known online tech assessment platforms that provide tools for managing and performing online examinations. We will examine the major areas where HackerEarth outperforms Mettl, thereby proving to be a great alternative to Mettl, in this comparison.

Also read: What Makes HackerEarth The Tech Behind Great Tech Teams

HackerEarth Vs Mettl

Features and functionality

HackerEarth believes in upgrading itself and providing the most effortless navigation and solutions to recruiters and candidates.

HackerEarth provides various tools and capabilities to create and administer online tests, such as programming tests, multiple-choice questions, coding challenges, and more. The software also has remote proctoring, automatic evaluation, and plagiarism detection tools (like detecting the use of ChatGPT in coding assessments). On the other side, Mettl offers comparable functionality but has restricted capabilities for coding challenges and evaluations.

Test creation and administration

HackerEarth: It has a user-friendly interface that is simple to use and navigate. It makes it easy for recruiters to handle evaluations without zero technical know-how. The HackerEarth coding platform is also quite flexible and offers a variety of pre-built exams, including coding tests, aptitude tests, and domain-specific examinations. It has a rich library of 17,000+ questions across 900+ skills, which is fully accessible by the hiring team. Additionally, it allows you to create custom questions yourself or use the available question libraries.

Also read: How To Create An Automated Assessment With HackerEarth

Mettl: It can be challenging for a hiring manager to use Mettl efficiently since Mettl provides limited assessment and question libraries. Also, their team creates the test for them rather than giving access to hiring managers. This results in a higher turnaround time and reduces test customization possibilities since the request has to go back to the team, they have to make the changes, and so forth.

Reporting and analytics

HackerEarth: You may assess applicant performance and pinpoint areas for improvement with the help of HackerEarth’s full reporting and analytics tools. Its personalized dashboards, visualizations, and data exports simplify evaluating assessment results and real-time insights.

Most importantly, HackerEarth includes code quality scores in candidate performance reports, which lets you get a deeper insight into a candidate’s capabilities and make the correct hiring decision. Additionally, HackerEarth provides a health score index for each question in the library to help you add more accuracy to your assessments. The health score is based on parameters like degree of difficulty, choice of the programming language used, number of attempts over the past year, and so on.

Mettl: Mettl online assessment tool provides reporting and analytics. However, there may be only a few customization choices available. Also, Mettle does not provide code quality assurance which means hiring managers have to check the whole code manually. There is no option to leverage question-based analytics and Mettl does not include a health score index for its question library.

Adopting this platform may be challenging if you want highly customized reporting and analytics solutions.

Also read: HackerEarth Assessments + The Smart Browser: Formula For Bulletproof Tech Hiring

Security and data privacy

HackerEarth: The security and privacy of user data are top priorities at HackerEarth. The platform protects data in transit and at rest using industry-standard encryption. Additionally, all user data is kept in secure, constantly monitored data centers with stringent access controls.

Along with these security measures, HackerEarth also provides IP limitations, role-based access controls, and multi-factor authentication. These features ensure that all activity is recorded and audited and that only authorized users can access sensitive data.

HackerEarth complies with several data privacy laws, such as GDPR and CCPA. The protection of candidate data is ensured by this compliance, which also enables businesses to fulfill their legal and regulatory responsibilities.

Mettl: The security and data privacy features of Mettl might not be as strong as those of HackerEarth. The platform does not provide the same selection of security measures, such as IP limitations or multi-factor authentication. Although the business asserts that it complies with GDPR and other laws, it cannot offer the same amount of accountability and transparency as other platforms.

Even though both HackerEarth and Mettl include security and data privacy measures, the Mettle alternative, HackerEarth’s platform is made to be more thorough, open, and legal. By doing this, businesses can better guarantee candidate data’s security and ability to fulfill legal and regulatory requirements.

Pricing and support

HackerEarth: To meet the demands of businesses of all sizes, HackerEarth offers a variety of customizable pricing options. The platform provides yearly and multi-year contracts in addition to a pay-as-you-go basis. You can select the price plan that best suits their demands regarding employment and budget.

HackerEarth offers chat customer support around the clock. The platform also provides a thorough knowledge base and documentation to assist users in getting started and troubleshooting problems.

Mettl: The lack of price information on Mettl’s website might make it challenging for businesses to decide whether the platform fits their budget. The organization also does not have a pay-as-you-go option, which might be problematic.

Mettl offers phone and emails customer assistance. However, the business website lacks information on support availability or response times. This lack of transparency may be an issue if you need prompt and efficient help.

User experience

HackerEarth: The interface on HackerEarth is designed to be simple for both recruiters and job seekers. As a result of the platform’s numerous adjustable choices for test creation and administration, you may design exams specifically suited to a job role. Additionally, the platform provides a selection of question types and test templates, making it simple to build and take exams effectively.

In terms of the candidate experience, HackerEarth provides a user-friendly interface that makes navigating the testing procedure straightforward and intuitive for applicants. As a result of the platform’s real-time feedback and scoring, applicants may feel more motivated and engaged during the testing process. The platform also provides several customization choices, like branding and message, which may assist recruiters in giving prospects a more exciting and tailored experience.

Mettl: The platform is intended to have a steeper learning curve than others and be more technical. It makes it challenging to rapidly and effectively construct exams and can be difficult for applicants unfamiliar with the platform due to its complex interface.

Additionally, Mettl does not provide real-time feedback or scoring, which might deter applicants from participating and being motivated by the testing process.

Also read: 6 Strategies To Enhance Candidate Engagement In Tech Hiring (+ 3 Unique Examples)

User reviews and feedback

According to G2, HackerEarth and Mettl have 4.4 reviews out of 5. Users have also applauded HackerEarth’s customer service. Many agree that the staff members are friendly and quick to respond to any problems or queries. Overall, customer evaluations and feedback for HackerEarth point to the platform as simple to use. Both recruiters and applicants find it efficient.

Mettl has received mixed reviews from users, with some praising the platform for its features and functionality and others expressing frustration with its complex and technical interface.

Free ebook to help you choose between Mettl and Mettle alternative, HackerEarth

May the best “brand” win!

Recruiting and selecting the ideal candidate demands a significant investment of time, attention, and effort.

This is where tech recruiting platforms like HackerEarth and Mettl have got you covered. They help streamline the whole process.Both HackerEarth and Mettl provide a wide variety of advanced features and capabilities for tech hiring.

We think HackerEarth is the superior choice. Especially, when contrasting the two platforms in terms of their salient characteristics and functioning. But, we may be biased!

So don’t take our word for it. Sign up for a free trial and check out HackerEarth’s offerings for yourself!

HackerEarth Assessments + The Smart Browser: Formula For Bulletproof Tech Hiring

Let’s face it—cheating on tests is quite common. While technology has made a lot of things easier in tech recruiting, it has also left the field wide open to malpractice. A 2020 report by ICAI shows that 32% of undergraduate students have cheated in some form on an online test.

It’s human nature to want to bend the rules a little bit. Which begs the question, how do you stay on top of cheating, plagiarism, and other forms of malpractice during the assessment process?

How do you ensure that take-home assessments and remote interviews stay authentic and credible? By relying on enhanced virtual supervision, of course!

HackerEarth Assessments has always been one step ahead when it comes to remote proctoring which is able to capture the nuances of candidate plagiarism. The recent advancements in technology (think generative AI) needed more robust proctoring features, so we went ahead and built The HackerEarth Smart Browser to ensure our assessments remain as foolproof as ever.

Presenting to you, the latest HackerEarth proctoring fix - The Smart Browser

Our Smart Browser is the chocolatey version of a plain donut when compared to a regular web browser. It is extra effective and comes packed with additional remote proctoring capabilities to increase the quality of your screening assessments.

The chances of a candidate cheating on a HackerEarth technical assessment are virtually zero with the latest features! Spilling all our secrets to show you why -

1. Sealed-off testing environment makes proctoring simpler

Sealed-off testing environment makes proctoring simpler

To get started with using the Smart Browser, enable the Smart Browser setting as shown above. This setting is available under the test proctoring section on the test overview page.

As you can see, several other proctoring settings such as disabling copy-paste, restricting candidates to full-screen mode, and logout on leaving the test interface are selected automatically.Now, every candidate you invite to take the assessment will only be able to do so through the Smart Browser. Candidates are prompted to download the Smart Browser from the link shared in the test invite mail.When the candidate needs to click on the ‘start test’ button on the launch test screen, it opens in the Smart Browser. The browser also prompts the candidate to switch to full-screen mode. Now, all candidates need to do is sign in and attempt the test, as usual.
Also read: 6 Ways Candidates Try To Outsmart A Remote Proctored Assessment

2. Eagle-eyed online test monitoring leaves no room for error

Eagle-eyed online test monitoring with the smart browser leaves no room for errorOur AI-enabled Smart Browser takes frequent snapshots via the webcam, throughout the assessment. Consequently, it is impossible to copy-paste code or impersonate a candidate.The browser prevents the following candidate actions and facilitates thorough monitoring of the assessment:
  • Screensharing the test window
  • Keeping other applications open during the test
  • Resizing the test window
  • Taking screenshots of the test window
  • Recording the test window
  • Using malicious keystrokes
  • Viewing OS notifications
  • Running the test window within a virtual machine
  • Operating browser developer tools
Any candidate actions attempting to switch tabs with the intent to copy-paste or use a generative AI like ChatGPT are shown a warning and captured in the candidate report.HackerEarth’s latest proctoring fixes bulletproof our assessment platform, making it one of the most reliable and accurate sources of candidate hiring in the market today.
Also read: 4 Ways HackerEarth Flags The Use Of ChatGPT In Tech Hiring Assessments

Experience reliable assessments with the Smart Browser!

There you have it - our newest offering that preserves the integrity of coding assessments and enables skill-first hiring, all in one go. Recruiters and hiring managers, this is one feature that you can easily rely on and can be sure that every candidate’s test score is a result of their ability alone.Curious to try out the Smart Browser? Well, don’t take our word for it. Head over here to check it out for yourself!

We also love hearing from our customers so don’t hesitate to leave us any feedback you might have.

Until then, happy hiring!
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What is Headhunting In Recruitment?: Types &amp; How Does It Work?

In today’s fast-paced world, recruiting talent has become increasingly complicated. Technological advancements, high workforce expectations and a highly competitive market have pushed recruitment agencies to adopt innovative strategies for recruiting various types of talent. This article aims to explore one such recruitment strategy – headhunting.

What is Headhunting in recruitment?

In headhunting, companies or recruitment agencies identify, engage and hire highly skilled professionals to fill top positions in the respective companies. It is different from the traditional process in which candidates looking for job opportunities approach companies or recruitment agencies. In headhunting, executive headhunters, as recruiters are referred to, approach prospective candidates with the hiring company’s requirements and wait for them to respond. Executive headhunters generally look for passive candidates, those who work at crucial positions and are not on the lookout for new work opportunities. Besides, executive headhunters focus on filling critical, senior-level positions indispensable to companies. Depending on the nature of the operation, headhunting has three types. They are described later in this article. Before we move on to understand the types of headhunting, here is how the traditional recruitment process and headhunting are different.

How do headhunting and traditional recruitment differ from each other?

Headhunting is a type of recruitment process in which top-level managers and executives in similar positions are hired. Since these professionals are not on the lookout for jobs, headhunters have to thoroughly understand the hiring companies’ requirements and study the work profiles of potential candidates before creating a list.

In the traditional approach, there is a long list of candidates applying for jobs online and offline. Candidates approach recruiters for jobs. Apart from this primary difference, there are other factors that define the difference between these two schools of recruitment.

AspectHeadhuntingTraditional RecruitmentCandidate TypePrimarily passive candidateActive job seekersApproachFocused on specific high-level rolesBroader; includes various levelsScopeproactive outreachReactive: candidates applyCostGenerally more expensive due to expertise requiredTypically lower costsControlManaged by headhuntersManaged internally by HR teams

All the above parameters will help you to understand how headhunting differs from traditional recruitment methods, better.

Types of headhunting in recruitment

Direct headhunting: In direct recruitment, hiring teams reach out to potential candidates through personal communication. Companies conduct direct headhunting in-house, without outsourcing the process to hiring recruitment agencies. Very few businesses conduct this type of recruitment for top jobs as it involves extensive screening across networks outside the company’s expanse.

Indirect headhunting: This method involves recruiters getting in touch with their prospective candidates through indirect modes of communication such as email and phone calls. Indirect headhunting is less intrusive and allows candidates to respond at their convenience.Third-party recruitment: Companies approach external recruitment agencies or executive headhunters to recruit highly skilled professionals for top positions. This method often leverages the company’s extensive contact network and expertise in niche industries.

How does headhunting work?

Finding highly skilled professionals to fill critical positions can be tricky if there is no system for it. Expert executive headhunters employ recruitment software to conduct headhunting efficiently as it facilitates a seamless recruitment process for executive headhunters. Most software is AI-powered and expedites processes like candidate sourcing, interactions with prospective professionals and upkeep of communication history. This makes the process of executive search in recruitment a little bit easier. Apart from using software to recruit executives, here are the various stages of finding high-calibre executives through headhunting.

Identifying the role

Once there is a vacancy for a top job, one of the top executives like a CEO, director or the head of the company, reach out to the concerned personnel with their requirements. Depending on how large a company is, they may choose to headhunt with the help of an external recruiting agency or conduct it in-house. Generally, the task is assigned to external recruitment agencies specializing in headhunting. Executive headhunters possess a database of highly qualified professionals who work in crucial positions in some of the best companies. This makes them the top choice of conglomerates looking to hire some of the best talents in the industry.

Defining the job

Once an executive headhunter or a recruiting agency is finalized, companies conduct meetings to discuss the nature of the role, how the company works, the management hierarchy among other important aspects of the job. Headhunters are expected to understand these points thoroughly and establish a clear understanding of their expectations and goals.

Candidate identification and sourcing

Headhunters analyse and understand the requirements of their clients and begin creating a pool of suitable candidates from their database. The professionals are shortlisted after conducting extensive research of job profiles, number of years of industry experience, professional networks and online platforms.

Approaching candidates

Once the potential candidates have been identified and shortlisted, headhunters move on to get in touch with them discreetly through various communication channels. As such candidates are already working at top level positions at other companies, executive headhunters have to be low-key while doing so.

Assessment and Evaluation

In this next step, extensive screening and evaluation of candidates is conducted to determine their suitability for the advertised position.

Interviews and negotiations

Compensation is a major topic of discussion among recruiters and prospective candidates. A lot of deliberation and negotiation goes on between the hiring organization and the selected executives which is facilitated by the headhunters.

Finalizing the hire

Things come to a close once the suitable candidates accept the job offer. On accepting the offer letter, headhunters help finalize the hiring process to ensure a smooth transition.

The steps listed above form the blueprint for a typical headhunting process. Headhunting has been crucial in helping companies hire the right people for crucial positions that come with great responsibility. However, all systems have a set of challenges no matter how perfect their working algorithm is. Here are a few challenges that talent acquisition agencies face while headhunting.

Common challenges in headhunting

Despite its advantages, headhunting also presents certain challenges:

Cost Implications: Engaging headhunters can be more expensive than traditional recruitment methods due to their specialized skills and services.

Time-Consuming Process: While headhunting can be efficient, finding the right candidate for senior positions may still take time due to thorough evaluation processes.

Market Competition: The competition for top talent is fierce; organizations must present compelling offers to attract passive candidates away from their current roles.

Although the above mentioned factors can pose challenges in the headhunting process, there are more upsides than there are downsides to it. Here is how headhunting has helped revolutionize the recruitment of high-profile candidates.

Advantages of Headhunting

Headhunting offers several advantages over traditional recruitment methods:

Access to Passive Candidates: By targeting individuals who are not actively seeking new employment, organisations can access a broader pool of highly skilled professionals.

Confidentiality: The discreet nature of headhunting protects both candidates’ current employment situations and the hiring organisation’s strategic interests.

Customized Search: Headhunters tailor their search based on the specific needs of the organization, ensuring a better fit between candidates and company culture.

Industry Expertise: Many headhunters specialise in particular sectors, providing valuable insights into market dynamics and candidate qualifications.

Conclusion

Although headhunting can be costly and time-consuming, it is one of the most effective ways of finding good candidates for top jobs. Executive headhunters face several challenges maintaining the g discreetness while getting in touch with prospective clients. As organizations navigate increasingly competitive markets, understanding the nuances of headhunting becomes vital for effective recruitment strategies. To keep up with the technological advancements, it is better to optimise your hiring process by employing online recruitment software like HackerEarth, which enables companies to conduct multiple interviews and evaluation tests online, thus improving candidate experience. By collaborating with skilled headhunters who possess industry expertise and insights into market trends, companies can enhance their chances of securing high-caliber professionals who drive success in their respective fields.

A Comprehensive Guide to External Sources of Recruitment

The job industry is not the same as it was 30 years ago. Progresses in AI and automation have created a new work culture that demands highly skilled professionals who drive innovation and work efficiently. This has led to an increase in the number of companies reaching out to external sources of recruitment for hiring talent. Over the years, we have seen several job aggregators optimise their algorithms to suit the rising demand for talent in the market and new players entering the talent acquisition industry. This article will tell you all about how external sources of recruitment help companies scout some of the best candidates in the industry, the importance of external recruitment in organizations across the globe and how it can be leveraged to find talent effectively.

Understanding external sources of recruitment

External sources refer to recruitment agencies, online job portals, job fairs, professional associations and any other organizations that facilitate seamless recruitment. When companies employ external recruitment sources, they access a wider pool of talent which helps them find the right candidates much faster than hiring people in-house. They save both time and effort in the recruitment process.

Online job portals

Online resume aggregators like LinkedIn, Naukri, Indeed, Shine, etc. contain a large database of prospective candidates. With the advent of AI, online external sources of recruitment have optimised their algorithms to show the right jobs to the right candidates. Once companies figure out how to utilise job portals for recruitment, they can expedite their hiring process efficiently.

Social Media

Ours is a generation that thrives on social media. To boost my IG presence, I have explored various strategies, from getting paid Instagram users to optimizing post timing and engaging with my audience consistently. Platforms like FB an IG have been optimized to serve job seekers and recruiters alike. The algorithms of social media platforms like Facebook and Instagram have been optimised to serve job seekers and recruiters alike. Leveraging them to post well-placed ads for job listings is another way to implement external sources of recruitment strategies.

Employee Referrals

Referrals are another great external source of recruitment for hiring teams. Encouraging employees to refer their friends and acquaintances for vacancies enables companies to access highly skilled candidates faster.

Campus Recruitment

Hiring freshers from campus allows companies to train and harness new talent. Campus recruitment drives are a great external recruitment resource where hiring managers can expedite the hiring process by conducting screening processes in short periods.

Recruitment Agencies

Companies who are looking to fill specific positions with highly skilled and experienced candidates approach external recruitment agencies or executive headhunters to do so. These agencies are well-equipped to look for suitable candidates and they also undertake the task of identifying, screening and recruiting such people.

Job Fairs

This is a win-win situation for job seekers and hiring teams. Job fairs allow potential candidates to understand how specific companies work while allowing hiring managers to scout for potential candidates and proceed with the hiring process if possible.

Importance of External Recruitment

The role of recruitment agencies in talent acquisition is of paramount importance. They possess the necessary resources to help companies find the right candidates and facilitate a seamless hiring process through their internal system. Here is how external sources of recruitment benefit companies.

Diversity of Skill Sets

External recruitment resources are a great way for companies to hire candidates with diverse professional backgrounds. They possess industry-relevant skills which can be put to good use in this highly competitive market.

Fresh Perspectives

Candidates hired through external recruitment resources come from varied backgrounds. This helps them drive innovation and run things a little differently, thus bringing in a fresh approach to any project they undertake.

Access to Specialized Talent

Companies cannot hire anyone to fill critical roles that require highly qualified executives. This task is assigned to executive headhunters who specialize in identifying and screening high-calibre candidates with the right amount of industry experience. Huge conglomerates and companies seek special talent through external recruiters who have carved a niche for themselves.

Now that you have learnt the different ways in which leveraging external sources of recruitment benefits companies, let’s take a look at some of the best practices of external recruitment to understand how to effectively use their resources.

Best Practices for Effective External Recruitment

Identifying, reaching out to and screening the right candidates requires a robust working system. Every system works efficiently if a few best practices are implemented. For example, hiring through social media platforms requires companies to provide details about their working environment, how the job is relevant to their audience and well-positioned advertisements. The same applies to the other external sources of recruitment. Here is how you can optimise the system to ensure an effective recruitment process.

Craft Clear and Compelling Job Descriptions

Detail Responsibilities: Clearly outline the key responsibilities and expectations for the role.

Highlight Company Culture: Include information about the company’s mission, values, and growth opportunities to attract candidates who align with your organizational culture.

Leverage Multiple Recruitment Channels

Diversify Sources: Use a mix of job boards, social media platforms, recruitment agencies, and networking events to maximize reach. Relying on a single source can limit your candidate pool.

Utilize Industry-Specific Platforms: In addition to general job boards, consider niche job sites that cater to specific industries or skill sets

Streamline the Application Process

Simplify Applications: Ensure that the application process is user-friendly. Lengthy or complicated forms can deter potential candidates from applying.

Mobile Optimization: Many candidates use mobile devices to apply for jobs, so ensure your application process is mobile-friendly.

Engage in Proactive Sourcing

Reach Out to Passive Candidates: Actively seek out candidates who may not be actively looking for a job but could be a great fit for your organization. Use LinkedIn and other professional networks for this purpose.

Maintain a Talent Pool: Keep a database of previous applicants and strong candidates for future openings, allowing you to reach out when new roles become available.

Utilize Social Media Effectively

Promote Job Openings: Use social media platforms like LinkedIn, Facebook, and Twitter to share job postings and engage with potential candidates. This approach can also enhance your employer brand

Conduct Background Checks: There are several ways of learning about potential candidates. Checking out candidate profiles on job boards like LinkedIn or social media platforms can give companies a better understanding of their potential candidates, thus confirming whether they are the right fit for the organization.

Implement Data-Driven Recruitment

Analyze Recruitment Metrics: Track key metrics such as time-to-hire, cost-per-hire, and source effectiveness. This data can help refine your recruitment strategies over time. Using external hiring software like HackeEarth can streamline the recruitment process, thus ensuring quality hires without having to indulge internal resources for the same.

Use Predictive Analytics: In this age of fast paced internet, everybody makes data-driven decisions. Using predictive analytics to study employee data will help companies predict future trends, thus facilitating a productive hiring process.

Conclusion

External sources of recruitment play a very important role in an organization’s talent acquisition strategy. By employing various channels of recruitment such as social media, employee referrals and campus recruitment drives, companies can effectively carry out their hiring processes. AI-based recruitment management systems also help in the process. Implementing best practices in external recruitment will enable organizations to enhance their hiring processes effectively while meeting their strategic goals.

Recruitment Chatbot: A How-to Guide for Recruiters

Recruiters constantly look for innovative ways and solutions to efficiently attract and engage top talent. One of the recruiter tools at their disposal is the recruitment chatbot. These digital assistants are revolutionizing how recruiters work.

Are you looking to add a chatbot to your hiring process?

Our comprehensive guide will take you through the essentials of a recruitment chatbot-from its role and benefits to planning and building one and optimizing your own.

The rise of AI in recruitment


Artificial intelligence (AI) is a transformative force reshaping most industries, if not all. Today, you'll find AI-generated marketing content, financial predictions, and even AI-powered contact center solutions. The recruitment field has not been left behind. Professionals are using AI technologies, such as machine learning, natural language processing (NLP), and predictive analytics, to enhance various aspects of recruitment.

A report by Facts & Factors projects the global AI recruitment market size will grow to $890.51 million by 2028.
AI-Recruitment-Market-Size
Source

Chatbots are a prime example of AI's practical application in the hiring process. They efficiently handle tasks that traditionally require constant human intervention-as we'll see in the next section.

Understanding recruitment chatbots


Now that you understand the role of AI in modern recruiting processes, let's focus on recruitment chatbots in particular.

What is a recruitment chatbot?

A recruitment chatbot is software designed to assist in the recruitment process by simulating human-like conversations and automating various tasks. The core functionalities include:
  • Asking candidates predefined questions about their qualifications, experience, and skills
  • Instantly responding to common questions about job openings, company culture, benefits, and application process
  • Automated interview scheduling process with human recruiters
  • Keeping qualified candidates informed about their application status
As of 2023, 35%-45% of companies were using AI recruitment tools. Here are two key notable ones:

General Motors


General Motors (GM) has a conversational hiring assistant, Ev-e, that appears as soon as you land on their career site.
General-Motors-Recruitment-Chatbot
Source

This AI-powered chatbot enabled GM to manage candidate communications efficiently. The company also lowered its interview scheduling time from 5-7 days to just 29 minutes. They also save around $2 million annually.

Hewlett Packard Enterprise


Hewlett Packard Enterprise (HPE) also has a great recruiting chatbot- the HPE Career Bot. It also pops up when you land on HPE's career site.
HP-Career-Chatbot
Source

HPE's goal was to use the chatbot to convert passive candidates into actual job applicants, and they did just that.

Within the first three months of its rollout, the career bot more than doubled its usual career site visitors, reaching over 950,000 candidates. Additionally, HPE converted 26% of job seekers into actual hires.

Benefits of using recruitment chatbots

> The key benefits of using a recruitment chatbot include:
  • Saving valuable time: Recruitment chatbots can automate repetitive tasks like answering FAQs. That speeds up the recruitment process, allowing recruiters to focus on other administrative tasks.
  • 24/7 availability: Unlike human recruiters, who can only work 9-10 hours daily, chatbots are available around the clock.
  • Better quality of hires: Chatbots use predetermined criteria for the initial candidate screening process, meaning they only approve qualified candidates.
  • Lower hiring costs: By automating various time-consuming tasks, chatbots help significantly reduce recruitment costs.
By doing all the above, recruitment chatbots help you save resources that would be unnecessarily wasted if you were using the traditional hiring process.

Planning your recruitment chatbot


Without a well-thought-out plan, even the most advanced chatbot will fall short of expectations.

Defining your chatbot's objectives

Before building your recruitment chatbot, clearly understand what you want to achieve with it. Setting specific objectives. Some objective examples are:
  • To screen applicants
  • To schedule interviews
  • To provide company information
To identify the ideal objectives for your recruitment chatbot, map out the candidate journey from their initial interaction to the final hiring decision. Then, identify the touchpoints where the chatbot can add value.

For instance, if you waste most of your time screening candidates, create a chatbot that can efficiently assess qualifications and experience.

Establish metrics to measure chatbot success. They should align with the goals you set. Some great metrics could be a reduction in time-to-hire or candidate satisfaction scores.

Designing conversations for optimal engagement

The next step is to design the conversations your chatbot might have with candidates. Cover everything from greetings to solutions to misunderstood queries.
  • Greetings: Always begin with a warm greeting.
  • Language: Avoid jargon and overly formal language. Use simple, straightforward, conversational language.
  • Guided approach: Steer the conversation, providing clear instructions. You can also include quick reply buttons for common responses.
  • Misunderstood queries: Ensure your chatbot handles misunderstandings gracefully by politely asking for clarification.
Don't forget to include options for the chatbot to escalate complex queries to a human recruiter.

Building your recruitment chatbot


Now, you're ready to build a recruitment chatbot that will improve your overall talent acquisition strategy.

Choosing the right platform

Start by choosing the right chatbot platform. For this, there are factors you must consider.

The first is whether it will help you build a chatbot that meets your needs. To determine this, refer to your objectives. For instance, if your objective is to reduce repetitive inquiries, ensure the platform has strong NLP capabilities to understand and respond to candidate queries naturally.

The other factor is your technical expertise. Determine whether you need a no-code/low-code platform or have the technical resources to build a custom solution.

The no-code or low-code solution with pre-built templates is ideal for recruitment teams without extensive technical expertise. The custom solution, on the other hand, suits teams with technical resources.

Besides that, consider the features each chatbot tool offers. For instance, does it have multi-channel support, customization options, integration capabilities, and detailed analytics? Also, ensure you choose an option within your budget.

Some popular chatbot platforms include Mya, Olivia, XOR, and Ideal.

Development and integration

Developing and integrating your recruitment chatbot is the next. Here's a step-by-step guide:
  1. Define the scope and workflows: Identify the ideal candidate touchpoints-where and how the chatbot will interact with potential candidates.
  2. Scriptwriting: Write scripts for possible interactions the chatbot will have with candidates. Use generative AI tools to generate great responses that align with your desired conversation tone and style in minutes.
  3. Build the chatbot: Use your chosen platform to build a chatbot that aligns with your workflow and scripts.
  4. Testing: Conduct thorough testing to identify and fix any issues. You can start with your team and then beta-test it with a small group of suitable candidates.
  5. Integrate with existing HR systems: Integrate your recruitment chatbot with your Applicant Tracking System (ATS), your calendar, among others.
Once you're confident in the chatbot's performance, roll it out to candidates.

Training and optimizing your chatbot


Continuously train and optimize your recruitment chatbot to keep it aligned with your goals, changing recruitment needs, and company policies. Let's break this down:

Training your chatbot with AI and Machine Learning

Start by collecting historical data from past interactions, such as emails, chat logs, and support tickets, to use as the initial training data set. Leverage the data to teach your chatbot how to understand and respond to various candidate inquiries.

The data should include a wide range of scenarios.

Also, use NLP to train your recruitment chatbot to understand and process human language. You can use NLP frameworks like AllenNLP, Apache OpenNLP, or Google's BERT.

Implement a continuous learning loop where your recruitment chatbot can learn from new interactions to expand its knowledge base and adjust its conversational strategies.

Monitoring and improving chatbot performance

Regularly monitor your recruitment chatbot interactions and metrics to improve your recruitment chatbot performance and ensure candidate satisfaction.

Constantly review your interaction logs to understand how candidates are interacting with the chatbot. Identify common issues or misunderstandings. You can also collect user feedback directly from candidates who have interacted with the chatbot.

Track metrics like response accuracy, conversation completion rate, candidate satisfaction scores, and time saved for recruiters. You can then use the valuable insights to refine the scripts, improve responses, and address the knowledge gaps.

Additionally, keep up with the latest trends and advancements in AI and recruitment technology to maintain the chatbot's relevance over time.

Legal and ethical considerations


Using AI in recruitment comes with legal and ethical challenges. These include:

Ensuring compliance and privacy

Ensure your chatbot complies with data protection laws and regulations to avoid unnecessary legal suits.

Most regulations require you to inform candidates about the personal data collected, how you will use it, and your data retention policy.

Popular regulations include the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and Canada's PIPEDA.

Addressing bias in AI

AI-driven recruitment tools can unknowingly carry on biases from the training data or algorithms. You must address these biases to ensure fair and equitable treatment of all candidates.

Use diverse and representative training data to reduce the risk of biased outcomes. Also, regularly audit your training data for biases related to gender, race, age, disability, or other protected characteristics.

Best practices and tips


Implementing a recruitment chatbot requires you to follow best practices to effectively meet your hiring goals while providing a positive candidate experience.

Dos and don'ts for recruitment chatbots

Here are some of the most essential tips and common pitfalls:

Dos


-Ensure your chatbot is user-friendly and capable of handling various inquiries at a go.

-Offer personalized experiences.

-Provide relevant and timely information.

-Ensure the chatbot is accessible to all candidates, including those with disabilities.

Don'ts


-Don't over-automate. Maintain a balance with human touchpoints

-Don't overwhelm candidates with too much information at once

Future trends in AI recruitment


The future of AI in recruitment looks promising, with trends such as advanced natural language processing (NLP). The advanced capabilities will allow chatbots to understand and respond to more complex queries.

Besides that, we can expect future chatbots to use more interactive content, like video intros, virtual reality (VR) job previews, or virtual workplace tours to boost candidate engagement. A company like McKinsey & Company is already using gamified pre-employment assessments.
McKinsey-Gamified-Recruitment-Chatbot
Source

We will also see more advanced AI-powered candidate matching that provides personalized job recommendations based on a candidate's skills, experience, and career aspirations.

Conclusion


Recruitment chatbots are revolutionizing the recruiting process. By automating routine tasks, providing instant responses, and offering data-driven insights, chatbots enhance both recruiters' and candidates' experiences.

As discussed in this guide, implementing a recruitment chatbot involves several crucial steps.

Define the objectives and design conversation paths. Next, choose your ideal platform and build your chatbot. After that, train and continuously optimize it to ensure it remains accurate and relevant. Also, ensure you're complying with the core legal and ethical considerations.

Now go build a recruitment chatbot that slashes your workload and gives your candidates a great experience.
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