Developer Insights

Data visualization packages in R-Part I

A good understanding of data is one of the key essentials to designing effective Machine Learning (ML) algorithms. Realizing the structure and properties of the data that you are working with is crucial in devising new methods that can solve your problem. Visualizing data includes the following:

Cleaning up the data
Structuring and arranging it
Plotting it to understand the granularity

R, one of the few widely-used programming languages for ML, has many data-visualization libraries.

In this article, we will explore two of the most commonly used packages in R for analyzing data—dplyr and tidyr.

Using dplyr and tidyr

dplyr and tidyr, created by Hadley Wickham and maintained by the RStudio team, offer a powerful set of tools for data manipulation. One of their best features is the pipeline operator %>%, which allows chaining multiple operations together in a clean and readable format.

tidyr Functions

`gather()`

Transforms wide-format data into long-format by collecting columns into key-value pairs.

gather(data, key, value, ..., na.rm = FALSE, convert = FALSE, factor_key = FALSE)
data %>% gather(key, value, ..., na.rm = FALSE, convert = FALSE, factor_key = FALSE)

key, value	Names of the columns to be created in output
`…`	Columns to gather. Use `-` to exclude specific columns
na.rm	If TRUE, rows with NA values will be discarded
convert	Convert key values to appropriate types
factor_key	Whether to treat key as a factor or character

`spread()`

Opposite of gather(); spreads key-value pairs into wide format.

spread(data, key, value, fill = NA, convert = FALSE, drop = TRUE, sep = NULL)

fill	Value used to fill in missing combinations
drop	Whether to drop unused factor levels
sep	String used to separate column names if not NULL

`separate()` & `unite()`

separate() splits a column into multiple columns based on a separator. unite() merges multiple columns into one.

dplyr Functions

`select()`

Choose specific columns based on name, pattern, or position.

`filter()`, `slice()`, `distinct()`, `sample_n()`, `sample_frac()`

Filter rows, remove duplicates, and take samples from the data.

`group_by()` & `summarise()`

group_by() creates groups, while summarise() computes summary statistics for each group.

summarise(df, avg = mean(column_name))

`mutate()`

Add or transform columns using expressions like:

mutate(new_col = col1 / col2)

Joins

Supports all major joins: left_join(), right_join(), inner_join(), full_join(), semi_join(), and anti_join().

`arrange()`

Sort data ascending or descending using desc().

Data Visualization with ggplot2

Bar Chart Example


ggplot(data = gather(stocks, stock, price, -time) %>%
       group_by(time) %>%
       summarise(avg = mean(price)),
       aes(x = time, y = avg, fill = time)) +
       geom_bar(stat = "identity")

Scatter Plot Example


qplot(time, avg,
      data = gather(stocks, stock, price, -time) %>%
             group_by(time) %>%
             summarise(avg = mean(price)),
      colour = 'red',
      main = "Avg change of stock price for each month",
      xlab = "month",
      ylab = "avg price")

Regression models help uncover hidden trends. Libraries like dplyr and tidyr don’t just clean your data—they boost your data intuition and enable better decisions.

In the next article, we'll explore more data-visualization libraries.

Developer Insights

How Artificial Intelligence is rapidly changing everything around you!

We live in an interesting era in the history of mankind. You will be surprised to know that Apollo 11, the computer that put Man on the Moon in 1969, whose assembly language code was recently published on Github, operated on 64KB memory whereas today’s kids have 64GB iPhones to click duckface selfies to upload on Instagram and play PokeMon Go, a viral game that marginally broke all time daily active users’ record in a week! Technically, 1 Million times more memory and 100 million times computational power at your disposal. After all, Moore’s law is nothing less than a super genius prediction.

Thought provoking extrapolation of the same Moore’s law, that says that the number of transistors in an integrated circuit and hence the computational power doubles itself every 2 years resulting into exponential technological growth, is applicable to the most evolving field of technology, Artificial Intelligence. For me, as the kid of Gen-Y, it is mind-blowing to think how the first movie ever was produced in the year my great grandfather was born, the first computer was built when my grandfather was still in his teens, the first Star Wars movie was released when my father learned fishing and how only last month, I blew my mind watching the first movie named Sunspring written by an AI program that christened itself as Benjamin. Not going to be long before I know, my kid wakes me up in the middle of the night someday and tells me, ‘Hey dad! One super intelligent robot called Trump has waged a war against humanity to destroy the entire human race.’ And WHAM! The most dreaded Apocalypse is a reality. Who knows?

If you are still optimistic and think that it is just a trippy thought experiment, here’s the generalized version of Moore’s law, depicted by Kurzweil as The Law of Accelerating Returns.

Kurzweil provides an interesting way of looking at the advancement of Artificial in terms of CPS achieved per $1000. The exponential nature of this curve can be visualized with respect to human intelligence and how quickly we are advancing towards the human level intelligence.

Not a long ago, we were struggling to artificially replicate the brain, read intelligence, of an insect and just so overwhelmingly, we are not too far from artificially achieving the intelligence of the most superior specie on the planet earth. What lies beyond that is a mystery for a layman but we indeed are living in the golden era of the exponential curve of technological progress. The singularity is near!

The journey so far hasn’t been easy. Ponder over this deep. Starting from the Big bang, to the birth of life on the earth, to development of human civilizations, to the million science experiments that went wrong along the progress including the first computer and the first lines of code, followed by a gazillion more, everything has contributed in making today’s Machine learn with humongous data to take intelligent decisions of its own, to probably build their own society tomorrow.

The Need of Artificial Intelligence

Have you ever been so lazy to be stalled on your bed with packets of tortilla chips and the latest episodes of Game of Thrones, that you just fantasized a remote control with multiple buttons to open the door or turn the fan on or do all that boring stuff? Oh wait, that still requires you to hold the remote and press the buttons, right? Gee, why don’t we have a robot that would just read our mind and do everything from household stuff to attending the unwanted guests without asking anything in return. Firstly, such robot will have to be super intelligent. Not only will it have to be efficient to perform routine tasks, but also understand your emotions viz-a-viz, mood swings and your behavioral pattern by observing you every minute and processing the data of your actions and emotions. Apart from the hard-coded seemingly basic set of functions, which in itself is a mammoth task, the machine will have to progressively learn by observations in order to perform as good as a smart human to serve you.

While a lot of this has been significantly achieved, it is still a very hard task for a machine to detect, segregate and arrange scented towels, hairdryers, Nutella box or contact lenses from a pile of junk than computing the complicated Euler product for a Riemann Zeta function. Machines can be entirely clueless and result into wrong outputs for what seems obvious that humans can solve in just a second’s glance.

You know how they say, “Don’t reinvent the wheel”, researchers have recently recreated a complex Quantum Physics experiment using AI just in an hour, that had won a Nobel prize in 2001 followed by years of determination and hard work by renowned Physicists like Einstein and Bose. We need AI to take care of trivial life problems so that we can invest our time and build a better AI to solve more important problems, like treating cancer or fighting against global warming. Fascinatingly enough, AI is actually everywhere; but more often than not we fail to see it. Because as John McCarthy, rightly says: “As soon as it works, no one calls it AI anymore.”

How AI is Everywhere Facilitated by Machine Learning

Right from a smartphone App that suggests you the nearby fast food outlet you might be interested in, to Facebook’s photo tagging Algorithm that detects your face with or without a beard, to Google’s self driving car, AI is everywhere and is deeply embedded in our lives without us realizing it. Our perceptions of AI are biased by Sci-Fi movies with evil machines trying to take over the galaxy. Intelligent machines designed to learn in order to become more intelligent by themselves to achieve Superintelligence is not hard to imagine. Technically, this would lie on the steepest slope of the exponential curve of intelligence versus time that we discussed before.

It is a beautiful realization that the roots of Artificial intelligence of a self driving car taking decisions that involve lives on the road lie within countless trivial and complicated Machine Learning algorithms that actually start with a few lines of code on your computer. My friend who had no background of computer science whatsoever before college, started learning programming in his sophomore year and took a long time before he could write fine algorithms in C++. He then started reading about Image processing, right from how a black and white image can be represented with a metric of numbers and went on writing a simple algorithm to detect a stable human hand. Soon with his growing interest, the human hand was replaced with colonoscopy images to robust deep learning algorithms that could detect cancer with image processing. His research paper got accepted in an international conference and has many other industrial applications.

Machine Learning and the Power of Big Data

With unmatched computational power machines can process and be trained to make decisions using big data and predictive modelling. Imagine a person having superpowers who can predict future of everything, the world would fall at their feet. In a more logical sense, if a machine can process humongous amount of historical and real time data with prediction models, and learns over time to get better and better, imagine, the power of big data is nothing less than magical.

Several industries vastly use Machine Learning to take data driven decisions and make life smarter with the power of data accumulated over the years. Healthcare has already been positively impacted with the tremendous amount of work in this field that has contributed in saving thousands of lives. From Governance to Economy to Healthcare, name a domain and you have smart multi-variable regression models backed by big data, performing predictive analysis. Super intelligent machines can now decide your fate to survive in a Multi-Billion dollar stock market. In a way, AI has started affecting our lives tangibly even without us realizing it, and if you look back, it really happened in the blink of an eye.

Whether we live to see the empire of Artificial Superintelligence that surpasses our brain and the human race ends up being the “biological boot loader for digital Superintelligence” OR we produce extraordinary artificial intelligence to look beyond galaxies and travel to future, only time will tell. But one thing is for sure, whatever happens, at the heart of it lie several complicated Algorithms that actually started with a few lines of code.

Developer Insights

IndiaHacks 2016 Offline Conference is here!

“While learning equips you, and practice improves your skills, competition helps you prove your worth”

We at HackerEarth strongly believe in the power of them all. We understand the value associated with learning, practicing and competing. With the same goals, we started our flagship event ‘IndiaHacks’ on January 8th, 2016.

IndiaHacks soon received a lot of enthusiasm and emerged as the largest conglomeration of developers. More than 1 lakh developers across the globe registered for IndiaHacks. It has been an amazing journey so far with tremendous zeal, tough competition, and global participation. The first phase is coming to an end and we are delighted with how the event has unfolded.

As much as we believe in competition, we also believe in preparing the participants and rewarding them for their efforts and triumphs. The phase 2 of IndiaHacks is an offline conference that will be held on 19th March at Vivanta by Taj, Yeshwanthpur. The conference will have experts from various domains of technology to talk about different topics and share their knowledge with the community. The experts will be a part of events such as tech talks, panel discussions, working sessions, hangouts etc. and will speak on a plethora of topics like data visualization, big data and analytics, artificial intelligence, machine learning, deep learning, fintech, competitive programming, robotics, scientific computing, open source, embedded systems programming etc.

It is a great opportunity to interact with them and gain knowledge in various domains.The conference will end with rewarding the best minds across each track.

The tickets to the conference are up for purchase and 100 early birds will receive a discount of 25% on each ticket.

Top 20 teams from each track will receive free entry to the conference. The competition doesn’t end here, there are other ways to win free tickets too.

Click on the link below to know more about the conference, what it has in store for you and what you can do to be a part of it.

https://www.hackerearth.com/indiahacks-conference/

Developer Insights

TRAI's verdict on net neutrality

The telecom service provider just sent out a notification that one can use their services only to call friends and family in Delhi and not in other parts of the country. How does that sound? Partial? Well, don’t worry it isn’t true. Why should the service provider decide who should I call from my phone? This post will try to demystify the Net Neutrality myth.

The internet works on a similar principle and the principle advocates for an open internet. One must be able to communicate freely across the internet. This principle is referred to as net neutrality. For the net to be neutral, ISPs and the government must treat all data on internet equal and not charge differential based on user, content, website, app etc.

There has been much hue and cry about net neutrality off late and the debate seemed to be growing exponentially over the past few months. With the biggest names in the media industry expressing their views on net neutrality, it has been the most discussed topic all over the internet. The debate started gaining attention with Airtel coming up with a zero plan that stated that the provider will charge for VOIP calls made through apps like Whatsapp and Skype, it also made certain apps free for the users. While they argued that Airtel zero is a marketing platform where the data charges will be paid by the companies whose apps are free, the others condemned it as against net neutrality. This led to Flipkart pulling itself out of the scheme.

The Telecom Regulatory Authority of India (TRAI) had initially come up with a consultation paper that aimed at setting up a regulatory framework for over the top (OTT) services in India like Whatsapp and Skype but was criticized on grounds that it is already regulated by the IT Act.

Finally, after a lot of debates TRAI has come up with a decision that is in favor of net neutrality.

On Monday, February 8th, 2016, they barred the service providers from charging differential prices for data services and hence phased out Airtel Zero and Facebook’s Free Basics in their current form.

The decision encompasses the following points:

No service provider can offer or charge discriminatory tariffs for data services on the basis of content.
No service provider shall enter into any arrangement, agreement or contract, by whatever name called, with any person, natural or legal, that results in discriminatory tariffs for data services being offered or charged by the service provider for the purpose of evading the prohibition in this regulation.
Reduced tariff for accessing or providing emergency services, or at times of public emergency has been permitted.
Financial disincentives for contravention of the regulation have also been specified.
TRAI may review these regulations after a period of two years.

This decision that favors net neutrality will also favor the users who are free to access any content on the web, after all, it is the worldwide web and access to all websites must be easy and hassle-free. It will also favor startups and new business owners by giving them the opportunity to showcase their products and services without being discriminated against the big giants that can easily pay money to be free to the users. Net neutrality hence supports a competitive marketplace. It also promotes freedom of speech.

A word with a Facebook spokesperson reveals that they are disappointed about TRAI’s decision but will make further efforts to promote their idea of 'Free Basics' for the unconnected. Telecom providers may also come up against the decision but for now, the battle is won and our Internet is free. This success can be attributed to our efforts to understand net neutrality and raising a voice against the abuse of our privileges by the influential giants. The victory of net neutrality is our victory.

Let’s celebrate this victory by sharing our joy by letting everyone know that the internet is infinite and we are free to use it according to our wish. And what better way to start than participating in some of the exciting challenges that we are conducting.

Developer Insights

IoT podcast with Srinivas Muktevi from Honeywell

The buzz about Internet of Things is gaining attention each day and the ones talking about it claim that its potential is not limited to how we live but also affects how we execute day-to-day tasks at our workplace.

Despite IoT being the talk of the town, there is still a lot of confusion about what exactly it is and how it impacts us and our work lives.

In general terminology, IoT is simply an increase in machine-to-machine communication by means of physical connectivity of devices embedded with WiFi capabilities and sensors. The immediate impact can be experienced with the wide availability of the internet, decreasing costs, and the penetration of smartphones. This is not all — the potential of the domain is wider than a layman can see. It extends from coffee machines to fitness trackers to jet planes and can be experienced in all walks of life, simple or complex.

We at HackerEarth took up a task to clear the haze around the topic and help the community understand IoT better. We conducted a podcast about IoT and how it impacts us. We had Mr. Srinivas Muktevi from Honeywell with us to talk to us about it. He provided an insight into the vast field and also told us how Honeywell plans to work on it. Below are the excerpts from the podcast:

Honeywell's interest in IoT and when did the emergence of IoT catch Honeywell's attention

How important will it be in the next 4-5 years to include the internet fabric?

Anticipating 20 billion devices by 2020, what kind of security, connectivity, hardware is required?

What will the IoT devices of the future look like and kind of advancements expected in coming years?

Security issues that IoT systems may pose

Skills required in an engineer in IoT domain and importance of hardware & software knowledge

The importance of user experience

Developer Insights

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

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:

How to Build a Python Bot

Use APIs to develop user applications quickly:

Practice with these bot-building challenges:

Tic Tac Toe
Hex
Dots & Boxes

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.

Meet our Authors

Get to know the experts behind our content. From industry leaders to tech enthusiasts, our authors share valuable insights, trends, and expertise to keep you informed and inspired.

Ruehie Jaiya Karri

Kumari Trishya

Hiring Strategies

7 Tech Recruiting Trends To Watch Out For In 2024

The last couple of years transformed how the world works and the tech industry is no exception. Remote work, a candidate-driven market, and automation are some of the tech recruiting trends born out of the pandemic.

While accepting the new reality and adapting to it is the first step, keeping up with continuously changing hiring trends in technology is the bigger challenge right now.

What does 2024 hold for recruiters across the globe? What hiring practices would work best in this post-pandemic world? How do you stay on top of the changes in this industry?

The answers to these questions will paint a clearer picture of how to set up for success while recruiting tech talent this year.

7 tech recruiting trends for 2024

6 Tech Recruiting Trends To Watch Out For In 2022

Recruiters, we’ve got you covered. Here are the tech recruiting trends that will change the way you build tech teams in 2024.

Trend #1—Leverage data-driven recruiting

Data-driven recruiting strategies are the answer to effective talent sourcing and a streamlined hiring process.

Talent acquisition leaders need to use real-time analytics like pipeline growth metrics, offer acceptance rates, quality and cost of new hires, and candidate feedback scores to reduce manual work, improve processes, and hire the best talent.

The key to capitalizing on talent market trends in 2024 is data. It enables you to analyze what’s working and what needs refinement, leaving room for experimentation.

Trend #2—Have impactful employer branding

98% of recruiters believe promoting company culture helps sourcing efforts as seen in our 2021 State Of Developer Recruitment report.

Having a strong employer brand that supports a clear Employer Value Proposition (EVP) is crucial to influencing a candidate’s decision to work with your company. Perks like upskilling opportunities, remote work, and flexible hours are top EVPs that attract qualified candidates.

A clear EVP builds a culture of balance, mental health awareness, and flexibility—strengthening your employer brand with candidate-first policies.

Trend #3—Focus on candidate-driven market

The pandemic drastically increased the skills gap, making tech recruitment more challenging. With the severe shortage of tech talent, candidates now hold more power and can afford to be selective.

Competitive pay is no longer enough. Use data to understand what candidates want—work-life balance, remote options, learning opportunities—and adapt accordingly.

Recruiters need to think creatively to attract and retain top talent.

Recommended read: What NOT To Do When Recruiting Fresh Talent

Trend #4—Have a diversity and inclusion oriented company culture

Diversity and inclusion have become central to modern recruitment. While urgent hiring can delay D&I efforts, long-term success depends on inclusive teams. Our survey shows that 25.6% of HR professionals believe a diverse leadership team helps build stronger pipelines and reduces bias.

McKinsey’s Diversity Wins report confirms this: top-quartile gender-diverse companies see 25% higher profitability, and ethnically diverse teams show 36% higher returns.

It's refreshing to see the importance of an inclusive culture increasing across all job-seeking communities, especially in tech. This reiterates that D&I is a must-have, not just a good-to-have.

—Swetha Harikrishnan, Sr. HR Director, HackerEarth

Trend #5—Embed automation and AI into your recruitment systems

With the rise of AI tools like ChatGPT, automation is being adopted across every business function—including recruiting.

Manual communication with large candidate pools is inefficient. In 2024, recruitment automation and AI-powered platforms will automate candidate nurturing and communication, providing a more personalized experience while saving time.

Trend #6—Conduct remote interviews

With 32.5% of companies planning to stay remote, remote interviewing is here to stay.

Remote interviews expand access to global talent, reduce overhead costs, and increase flexibility—making the hiring process more efficient for both recruiters and candidates.

Trend #7—Be proactive in candidate engagement

Delayed responses or lack of updates can frustrate candidates and impact your brand. Proactive communication and engagement with both active and passive candidates are key to successful recruiting.

As recruitment evolves, proactive candidate engagement will become central to attracting and retaining talent. In 2023 and beyond, companies must engage both active and passive candidates through innovative strategies and technologies like chatbots and AI-powered systems. Building pipelines and nurturing relationships will enhance employer branding and ensure long-term hiring success.

—Narayani Gurunathan, CEO, PlaceNet Consultants

Recruiting Tech Talent Just Got Easier With HackerEarth

Recruiting qualified tech talent is tough—but we’re here to help. HackerEarth for Enterprises offers an all-in-one suite that simplifies sourcing, assessing, and interviewing developers.

Our tech recruiting platform enables you to:

Tap into a 6 million-strong developer community
Host custom hackathons to engage talent and boost your employer brand
Create online assessments to evaluate 80+ tech skills
Use dev-friendly IDEs and proctoring for reliable evaluations
Benchmark candidates against a global community
Conduct live coding interviews with FaceCode, our collaborative coding interview tool
Guide upskilling journeys via our Learning and Development platform
Integrate seamlessly with all leading ATS systems
Access 24/7 support with a 95% satisfaction score

Recommended read: The A-Zs Of Tech Recruiting - A Guide

Staying ahead of tech recruiting trends, improving hiring processes, and adapting to change is the way forward in 2024. Take note of the tips in this article and use them to build a future-ready hiring strategy.

Ready to streamline your tech recruiting? Try HackerEarth for Enterprises today.

Hiring Strategies

(Part 2) Essential Questions To Ask When Interviewing Developers In 2021

The first part of this blog stresses the importance of asking the right technical interview questions to assess a candidate’s coding skills. But that alone is not enough. If you want to hire the crème de la crème of the developer talent out there, you have to look for a well-rounded candidate.

Honest communication, empathy, and passion for their work are equally important as a candidate’s technical knowledge. Soft skills are like the cherry on top. They set the best of the candidates apart from the rest.

Re-examine how you are vetting your candidates. Identify the gaps in your interviews. Once you start addressing these gaps, you find developers who have the potential to be great. And those are exactly the kind of people that you want to work with!

Let’s get to it, shall we?

What constitutes a good interview question?

An ideal interview should reveal a candidate’s personality along with their technical knowledge. To formulate a comprehensive list of questions, keep in mind three important characteristics.

Questions are open-ended – questions like, “What are some of the programming languages you’re comfortable with,” instead of “Do you know this particular programming language” makes the candidate feel like they’re in control. It is also a chance to let them reply to your question in their own words.
They address the behavioral aspects of a candidate – ensure you have a few questions on your list that allow a candidate to describe a situation. A situation where a client was unhappy or a time when the developer learned a new technology. Such questions help you assess if the candidate is a good fit for the team.
There is no right or wrong answer – it is important to have a structured interview process in place. But this does not mean you have a list of standard answers in mind that you’re looking for. How candidates approach your questions shows you whether they have the makings of a successful candidate. Focus on that rather than on the actual answer itself.

Designing a conversation around these buckets of interview questions brings you to my next question, “What should you look for in each candidate to spot the best ones?”

Hire GREAT developers by asking the right questions

Before we dive deep into the interview questions, we have to think about a few things that have changed. COVID-19 has rendered working from home the new normal for the foreseeable future. As a recruiter, the onus falls upon you to understand whether the developer is comfortable working remotely and has the relevant resources to achieve maximum productivity.

#1 How do you plan your day?

Remote work gives employees the option to be flexible. You don’t have to clock in 9 hours a day as long as you get everything done on time. A developer who hasn’t always been working remotely, but has a routine in place, understands the pitfalls of working from home. It is easy to get distracted and having a schedule to fall back on ensures good productivity.

#2 Do you have experience using tools for collaboration and remote work?

Working from home reduces human interaction heavily. There is no way to just go up to your teammate’s desk and clarify issues. Virtual communication is key to getting work done. Look for what kind of remote working tools your candidate is familiar with and if they know what collaborative tools to use for different tasks.

Value-based interview questions to ask

We went around and spoke to our engineering team, and the recruiting team to see what questions they abide by; what they think makes any candidate tick.

The result? – a motley group of questions that aim to reveal the candidate’s soft skills, in addition to typical technical interview questions and test tasks.

#3 Please describe three recent projects that you worked on. What were the most interesting and challenging parts?

This is an all-encompassing question in that it lets the candidate explain at length about their work ethic—thought process, handling QA, working with a team, and managing user feedback. This also lets you dig enough to assess whether the candidate is taking credit for someone else's work or not.

#4 You’ve worked long and hard to deliver a complex feature for a client and they say it’s not what they asked for. How would you take it?

A good developer will take it in their stride, work closely with the client to find the point of disconnect, and sort out the issue. There are so many things that could go wrong or not be to the client’s liking, and it falls on the developer to remain calm and create solutions.

#5 What new programming languages or technologies have you learned recently?

While being certified in many programming languages doesn't guarantee a great developer, it still is an important technical interview question to ask. It helps highlight a thirst for knowledge and shows that the developer is eager to learn new things.

#6 What does the perfect release look like? Who is involved and what is your role?

Have the developer take you through each phase of a recent software development lifecycle. Ask them to explain their specific role in each phase in this release. This will give you an excellent perspective into a developer’s mind. Do they talk about the before and after of the release? A skilled developer would. The chances of something going wrong in a release are very high. How would the developer react? Will they be able to handle the pressure?

SUBSCRIBE to the HackerEarth blog and enrich your monthly reading with our free e-newsletter – Fresh, insightful and awesome articles straight into your inbox from around the tech recruiting world!

#7 Tell me about a time when you had to convince your lead to try a different approach?

As an example of a behavioral interview question, this is a good one. The way a developer approaches this question speaks volumes about how confident they are expressing their views, and how succinct they are in articulating those views.

#8 What have you done with all the extra hours during the pandemic?

Did you binge-watch your way through the pandemic? I’m sure every one of us has done this. Indulge in a lighthearted conversation with your candidate. This lets them talk about something they are comfortable with. Maybe they learned a new skill or took up a hobby. Get to know a candidate’s interests and little pleasures for a more rounded evaluation.

Over to you! Now that you know what aspects of a candidate to focus on, you are well-equipped to bring out the best in each candidate in their interviews. A mix of strong technical skills and interpersonal qualities is how you spot good developers for your team.

If you have more pressing interview questions to add to this list of ours, please write to us at contact@hackerearth.com.

(Part 1) Essential Questions To Ask When Recruiting Developers In 2021

The minute a developer position opens up, recruiters feel a familiar twinge of fear run down their spines. They recall their previous interview experiences, and how there seems to be a blog post a month that goes viral about bad developer interviews.

While hiring managers, especially the picky ones, would attribute this to a shortage of talented developers, what if the time has come to rethink your interview process? What if recruiters and hiring managers put too much stock into bringing out the technical aspects of each candidate and don’t put enough emphasis on their soft skills?

A report by Robert Half shows that 86% of technology leaders say it’s challenging to find IT talent. Interviewing developers should be a rewarding experience, not a challenging one. If you don’t get caught up in asking specific questions and instead design a simple conversation to gauge a candidate’s way of thinking, it throws up a lot of good insight and makes it fun too.

Developer Hiring Statistics

Asking the right technical interview questions when recruiting developers is important but so is clear communication, good work ethic, and alignment with your organization’s goals.

Let us first see what kind of technical interview questions are well-suited to revealing the coding skills and knowledge of any developer, and then tackle the behavioral aspects of the candidate that sets them apart from the rest.

Recruit GREAT developers by asking the right questions

Here are some technical interview questions that you should ask potential software engineers when interviewing.

#1 Write an algorithm for the following

Minimum Stack - Design a stack that provides 4 functions - push(item), pop, peek, and minimum, all in constant order time complexity. Then move on to coding the actual solution.
Kth Largest Element in an array - This is a standard problem with multiple solutions of best time complexity orders where N log(K) is a common one and O(N) + K log(N) is a lesser-known order. Both solutions are acceptable, not directly comparable to each other, and better than N log(N), which is sorting an array and fetching the Kth element.
Top View of a Binary Tree - Given a root node of the binary tree, return the set of all elements that will get wet if it rains on the tree. Nodes having any nodes directly above them will not get wet.
Internal implementation of a hashtable like a map/dictionary - A candidate needs to specify how key-value pairs are stored, hashing is used and collisions are handled. A good developer not only knows how to use this concept but also how it works. If the developer also knows how the data structure scales when the number of records increases in the hashtable, that is a bonus.

Algorithms demonstrate a candidate’s ability to break down a complex problem into steps. Reasoning and pattern recognition capabilities are some more factors to look for when assessing a candidate. A good candidate can code his thought process of the algorithm finalized during the discussion.

Looking for a great place to hire developers in the US? Try Jooble!

#2 Formulate solutions for the below low-level design (LLD) questions

What is LLD? In your own words, specify the different aspects covered in LLD.
Design a movie ticket booking application like BookMyShow. Ensure that your database schema is tailored for a theatre with multiple screens and takes care of booking, seat availability, seat arrangement, and seat locking. Your solution does not have to extend to the payment option.
Design a basic social media application. Design database schema and APIs for a platform like Twitter with features for following a user, tweeting a post, seeing your tweet, and seeing a user's tweet.

Such questions do not have a right or wrong answer. They primarily serve to reveal a developer’s thought process and the way they approach a problem.

Recommended read: Hardest Tech Roles to Fill (+ solutions!)

#3 Some high-level design (HLD) questions

What do you understand by HLD? Can you specify the difference between LLD and HLD?
Design a social media application. In addition to designing a platform like Twitter with features for following a user, tweeting a post, seeing your tweet, and seeing a user's tweet, design a timeline. After designing a timeline where you can see your followers’ tweets, scale it for a larger audience. If you still have time, try to scale it for a celebrity use case.
Design for a train ticket booking application like IRCTC. Incorporate auth, features to choose start and end stations, view available trains and available seats between two stations, save reservation of seats from start to end stations, and lock them till payment confirmation.
How will you design a basic relational database? The database should support tables, columns, basic field types like integer and text, foreign keys, and indexes. The way a developer approaches this question is important. A good developer designs a solution around storage and memory management.

Here’s a pro-tip for you. LLD questions can be answered by both beginners and experienced developers. Mostly, senior developers can be expected to answer HLD questions. Choose your interview questions set wisely, and ask questions relevant to your candidate’s experience.

#4 Have you ever worked with SQL? Write queries for a specific use case that requires multiple joins.

Example: Create a table with separate columns for student name, subject, and marks scored. Return student names and ranks of each student. The rank of a student depends on the total of marks in all subjects.

Not all developers would have experience working with SQL but some knowledge about how data is stored/structured is useful. Developers should be familiar with simple concepts like joins, retrieval queries, and the basics of DBMS.

#5 What do you think is wrong with this code?

Instead of asking developer candidates to write code on a piece of paper (which is outdated, anyway), ask them to debug existing code. This is another way to assess their technical skills. Place surreptitious errors in the code and evaluate their attention to detail.

Now that you know exactly what technical skills to look for and when questions to ask when interviewing developers, the time has come to assess the soft skills of these candidates. Part 2 of this blog throws light on the how and why of evaluating candidates based on their communication skills, work ethic, and alignment with the company’s goals.

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Hiring Strategies

Best Pre-Employment Assessments: Optimizing Your Hiring Process for 2024

In today's competitive talent market, attracting and retaining top performers is crucial for any organization's success. However, traditional hiring methods like relying solely on resumes and interviews may not always provide a comprehensive picture of a candidate's skills and potential. This is where pre-employment assessments come into play.

What is Pre-Employement Assessment?

Pre-employment assessments are standardized tests and evaluations administered to candidates before they are hired. These assessments can help you objectively measure a candidate's knowledge, skills, abilities, and personality traits, allowing you to make data-driven hiring decisions.

By exploring and evaluating the best pre-employment assessment tools and tests available, you can:

Improve the accuracy and efficiency of your hiring process.
Identify top talent with the right skills and cultural fit.
Reduce the risk of bad hires.
Enhance the candidate experience by providing a clear and objective evaluation process.

This guide will provide you with valuable insights into the different types of pre-employment assessments available and highlight some of the best tools, to help you optimize your hiring process for 2024.

Why pre-employment assessments are key in hiring

While resumes and interviews offer valuable insights, they can be subjective and susceptible to bias. Pre-employment assessments provide a standardized and objective way to evaluate candidates, offering several key benefits:

Improved decision-making:

By measuring specific skills and knowledge, assessments help you identify candidates who possess the qualifications necessary for the job.
Reduced bias:

Standardized assessments mitigate the risks of unconscious bias that can creep into traditional interview processes.
Increased efficiency:

Assessments can streamline the initial screening process, allowing you to focus on the most promising candidates.
Enhanced candidate experience:

When used effectively, assessments can provide candidates with a clear understanding of the required skills and a fair chance to showcase their abilities.

Types of pre-employment assessments

There are various types of pre-employment assessments available, each catering to different needs and objectives. Here's an overview of some common types:

1. Skill Assessments:

Technical Skills: These assessments evaluate specific technical skills and knowledge relevant to the job role, such as programming languages, software proficiency, or industry-specific expertise. HackerEarth offers a wide range of validated technical skill assessments covering various programming languages, frameworks, and technologies.
Soft Skills: These employment assessments measure non-technical skills like communication, problem-solving, teamwork, and critical thinking, crucial for success in any role.

2. Personality Assessments:

These employment assessments can provide insights into a candidate's personality traits, work style, and cultural fit within your organization.

3. Cognitive Ability Tests:

These tests measure a candidate's general mental abilities, such as reasoning, problem-solving, and learning potential.

4. Integrity Assessments:

These employment assessments aim to identify potential risks associated with a candidate's honesty, work ethic, and compliance with company policies.

By understanding the different types of assessments and their applications, you can choose the ones that best align with your specific hiring needs and ensure you hire the most qualified and suitable candidates for your organization.

Leading employment assessment tools and tests in 2024

Choosing the right pre-employment assessment tool depends on your specific needs and budget. Here's a curated list of some of the top pre-employment assessment tools and tests available in 2024, with brief overviews:

HackerEarth:

A comprehensive platform offering a wide range of validated skill assessments in various programming languages, frameworks, and technologies. It also allows for the creation of custom assessments and integrates seamlessly with various recruitment platforms.
SHL:

Provides a broad selection of assessments, including skill tests, personality assessments, and cognitive ability tests. They offer customizable solutions and cater to various industries.
Pymetrics:

Utilizes gamified assessments to evaluate cognitive skills, personality traits, and cultural fit. They offer a data-driven approach and emphasize candidate experience.
Wonderlic:

Offers a variety of assessments, including the Wonderlic Personnel Test, which measures general cognitive ability. They also provide aptitude and personality assessments.
Harver:

An assessment platform focusing on candidate experience with video interviews, gamified assessments, and skills tests. They offer pre-built assessments and customization options.

Remember: This list is not exhaustive, and further research is crucial to identify the tool that aligns best with your specific needs and budget. Consider factors like the types of assessments offered, pricing models, integrations with your existing HR systems, and user experience when making your decision.

Choosing the right pre-employment assessment tool

Instead of full individual tool reviews, consider focusing on 2–3 key platforms. For each platform, explore:

Target audience: Who are their assessments best suited for (e.g., technical roles, specific industries)?
Types of assessments offered: Briefly list the available assessment categories (e.g., technical skills, soft skills, personality).
Key features: Highlight unique functionalities like gamification, custom assessment creation, or seamless integrations.
Effectiveness: Briefly mention the platform's approach to assessment validation and reliability.
User experience: Consider including user reviews or ratings where available.

Comparative analysis of assessment options

Instead of a comprehensive comparison, consider focusing on specific use cases:

Technical skills assessment:

Compare HackerEarth and Wonderlic based on their technical skill assessment options, focusing on the variety of languages/technologies covered and assessment formats.
Soft skills and personality assessment:

Compare SHL and Pymetrics based on their approaches to evaluating soft skills and personality traits, highlighting any unique features like gamification or data-driven insights.
Candidate experience:

Compare Harver and Wonderlic based on their focus on candidate experience, mentioning features like video interviews or gamified assessments.

Additional tips:

Encourage readers to visit the platforms' official websites for detailed features and pricing information.
Include links to reputable third-party review sites where users share their experiences with various tools.

Best practices for using pre-employment assessment tools

Integrating pre-employment assessments effectively requires careful planning and execution. Here are some best practices to follow:

Define your assessment goals:

Clearly identify what you aim to achieve with assessments. Are you targeting specific skills, personality traits, or cultural fit?
Choose the right assessments:

Select tools that align with your defined goals and the specific requirements of the open position.
Set clear expectations:

Communicate the purpose and format of the assessments to candidates in advance, ensuring transparency and building trust.
Integrate seamlessly:

Ensure your chosen assessment tool integrates smoothly with your existing HR systems and recruitment workflow.
Train your team:

Equip your hiring managers and HR team with the knowledge and skills to interpret assessment results effectively.

Interpreting assessment results accurately

Assessment results offer valuable data points, but interpreting them accurately is crucial for making informed hiring decisions. Here are some key considerations:

Use results as one data point:

Consider assessment results alongside other information, such as resumes, interviews, and references, for a holistic view of the candidate.
Understand score limitations:

Don't solely rely on raw scores. Understand the assessment's validity and reliability and the potential for cultural bias or individual test anxiety.
Look for patterns and trends:

Analyze results across different assessments and identify consistent patterns that align with your desired candidate profile.
Focus on potential, not guarantees:

Assessments indicate potential, not guarantees of success. Use them alongside other evaluation methods to make well-rounded hiring decisions.

Choosing the right pre-employment assessment tools

Selecting the most suitable pre-employment assessment tool requires careful consideration of your organization's specific needs. Here are some key factors to guide your decision:

Industry and role requirements:

Different industries and roles demand varying skill sets and qualities. Choose assessments that target the specific skills and knowledge relevant to your open positions.
Company culture and values:

Align your assessments with your company culture and values. For example, if collaboration is crucial, look for assessments that evaluate teamwork and communication skills.
Candidate experience:

Prioritize tools that provide a positive and smooth experience for candidates. This can enhance your employer brand and attract top talent.

Budget and accessibility considerations

Budget and accessibility are essential factors when choosing pre-employment assessments:

Budget:

Assessment tools come with varying pricing models (subscriptions, pay-per-use, etc.). Choose a tool that aligns with your budget and offers the functionalities you need.
Accessibility:

Ensure the chosen assessment is accessible to all candidates, considering factors like language options, disability accommodations, and internet access requirements.

Additional Tips:

Free trials and demos: Utilize free trials or demos offered by assessment platforms to experience their functionalities firsthand.
Consult with HR professionals: Seek guidance from HR professionals or recruitment specialists with expertise in pre-employment assessments.
Read user reviews and comparisons: Gain insights from other employers who use various assessment tools.

By carefully considering these factors, you can select the pre-employment assessment tool that best aligns with your organizational needs, budget, and commitment to an inclusive hiring process.

Remember, pre-employment assessments are valuable tools, but they should not be the sole factor in your hiring decisions. Use them alongside other evaluation methods and prioritize building a fair and inclusive hiring process that attracts and retains top talent.

Future trends in pre-employment assessments

The pre-employment assessment landscape is constantly evolving, with innovative technologies and practices emerging. Here are some potential future trends to watch:

Artificial intelligence (AI):

AI-powered assessments can analyze candidate responses, written work, and even resumes, using natural language processing to extract relevant insights and identify potential candidates.
Adaptive testing:

These assessments adjust the difficulty level of questions based on the candidate's performance, providing a more efficient and personalized evaluation.
Micro-assessments:

Short, focused assessments delivered through mobile devices can assess specific skills or knowledge on-the-go, streamlining the screening process.
Gamification:

Engaging and interactive game-based elements can make the assessment experience more engaging and assess skills in a realistic and dynamic way.

Conclusion

Pre-employment assessments, when used thoughtfully and ethically, can be a powerful tool to optimize your hiring process, identify top talent, and build a successful workforce for your organization. By understanding the different types of assessments available, exploring top-rated tools like HackerEarth, and staying informed about emerging trends, you can make informed decisions that enhance your ability to attract, evaluate, and hire the best candidates for the future.

Hiring Strategies

Tech Layoffs: What To Expect In 2024

Layoffs in the IT industry are becoming more widespread as companies fight to remain competitive in a fast-changing market; many turn to layoffs as a cost-cutting measure. Last year, 1,000 companies including big tech giants and startups, laid off over two lakhs of employees. But first, what are layoffs in the tech business, and how do they impact the industry?

Tech layoffs are the termination of employment for some employees by a technology company. It might happen for various reasons, including financial challenges, market conditions, firm reorganization, or the after-effects of a pandemic. While layoffs are not unique to the IT industry, they are becoming more common as companies look for methods to cut costs while remaining competitive.

The consequences of layoffs in technology may be catastrophic for employees who lose their jobs and the firms forced to make these difficult decisions. Layoffs can result in the loss of skill and expertise and a drop in employee morale and productivity. However, they may be required for businesses to stay afloat in a fast-changing market.

This article will examine the reasons for layoffs in the technology industry, their influence on the industry, and what may be done to reduce their negative impacts. We will also look at the various methods for tracking tech layoffs.

What are tech layoffs?

The term "tech layoff" describes the termination of employees by an organization in the technology industry. A company might do this as part of a restructuring during hard economic times.

In recent times, the tech industry has witnessed a wave of significant layoffs, affecting some of the world’s leading technology companies, including Amazon, Microsoft, Meta (formerly Facebook), Apple, Cisco, SAP, and Sony. These layoffs are a reflection of the broader economic challenges and market adjustments facing the sector, including factors like slowing revenue growth, global economic uncertainties, and the need to streamline operations for efficiency.

Each of these tech giants has announced job cuts for various reasons, though common themes include restructuring efforts to stay competitive and agile, responding to over-hiring during the pandemic when demand for tech services surged, and preparing for a potentially tough economic climate ahead. Despite their dominant positions in the market, these companies are not immune to the economic cycles and technological shifts that influence operational and strategic decisions, including workforce adjustments.

This trend of layoffs in the tech industry underscores the volatile nature of the tech sector, which is often at the mercy of rapid changes in technology, consumer preferences, and the global economy. It also highlights the importance of adaptability and resilience for companies and employees alike in navigating the uncertainties of the tech landscape.

Causes for layoffs in the tech industry

Why are tech employees suffering so much?

Yes, the market is always uncertain, but why resort to tech layoffs?

Various factors cause tech layoffs, including company strategy changes, market shifts, or financial difficulties. Companies may lay off employees if they need help to generate revenue, shift their focus to new products or services, or automate certain jobs.

In addition, some common reasons could be:

Financial struggles

Currently, the state of the global market is uncertain due to economic recession, ongoing war, and other related phenomena. If a company is experiencing financial difficulties, only sticking to pay cuts may not be helpful—it may need to reduce its workforce to cut costs.

Also, read: 6 Steps To Create A Detailed Recruiting Budget (Template Included)

Changes in demand

The tech industry is constantly evolving, and companies would have to adjust their workforce to meet changing market conditions. For instance, companies are adopting remote work culture, which surely affects on-premises activity, and companies could do away with some number of tech employees at the backend.

Restructuring

Companies may also lay off employees as part of a greater restructuring effort, such as spinning off a division or consolidating operations.

Automation

With the advancement in technology and automation, some jobs previously done by human labor may be replaced by machines, resulting in layoffs.

Mergers and acquisitions

When two companies merge, there is often overlap in their operations, leading to layoffs as the new company looks to streamline its workforce.

But it's worth noting that layoffs are not exclusive to the tech industry and can happen in any industry due to uncertainty in the market.

Will layoffs increase in 2024?

It is challenging to estimate the rise or fall of layoffs. The overall state of the economy, the health of certain industries, and the performance of individual companies will play a role in deciding the degree of layoffs in any given year.

But it is also seen that, in the first 15 days of this year, 91 organizations laid off over 24,000 tech workers, and over 1,000 corporations cut down more than 150,000 workers in 2022, according to an Economic Times article.

The COVID-19 pandemic caused a huge economic slowdown and forced several businesses to downsize their employees. However, some businesses rehired or expanded their personnel when the world began to recover.

So, given the current level of economic uncertainty, predicting how the situation will unfold is difficult.

Also, read: 4 Images That Show What Developers Think Of Layoffs In Tech

What types of companies are prone to tech layoffs?

Tech layoffs can occur in organizations of all sizes and various areas.

Following are some examples of companies that have experienced tech layoffs in the past:

Large tech firms

Companies such as IBM, Microsoft, Twitter, Better.com, Alibaba, and HP have all experienced layoffs in recent years as part of restructuring initiatives or cost-cutting measures.

Market scenarios are still being determined after Elon Musk's decision to lay off employees. Along with tech giants, some smaller companies and startups have also been affected by layoffs.

Startups

Because they frequently work with limited resources, startups may be forced to lay off staff if they cannot get further funding or need to pivot due to market downfall.

Small and medium-sized businesses

Small and medium-sized businesses face layoffs due to high competition or if the products/services they offer are no longer in demand.

Companies in certain industries

Some sectors of the technological industry, such as the semiconductor industry or automotive industry, may be more prone to layoffs than others.

Companies that lean on government funding

Companies that rely significantly on government contracts may face layoffs if the government cuts technology spending or contracts are not renewed.

How to track tech layoffs?

You can’t stop tech company layoffs, but you should be keeping track of them. We, HR professionals and recruiters, can also lend a helping hand in these tough times by circulating “layoff lists” across social media sites like LinkedIn and Twitter to help people land jobs quicker. Firefish Software put together a master list of sources to find fresh talent during the layoff period.

Because not all layoffs are publicly disclosed, tracking tech industry layoffs can be challenging, and some may go undetected. There are several ways to keep track of tech industry layoffs:

Use tech layoffs tracker

Layoff trackers like thelayoff.com and layoffs.fyi provide up-to-date information on layoffs.

In addition, they aid in identifying trends in layoffs within the tech industry. It can reveal which industries are seeing the most layoffs and which companies are the most affected.

Companies can use layoff trackers as an early warning system and compare their performance to that of other companies in their field.

News articles

Because many news sites cover tech layoffs as they happen, keeping a watch on technology sector stories can provide insight into which organizations are laying off employees and how many individuals have been affected.

Social media

Organizations and employees frequently publish information about layoffs in tech on social media platforms; thus, monitoring companies' social media accounts or following key hashtags can provide real-time updates regarding layoffs.

Online forums and communities

There are online forums and communities dedicated to discussing tech industry news, and they can be an excellent source of layoff information.

Government reports

Government agencies such as the Bureau of Labor Statistics (BLS) publish data on layoffs and unemployment, which can provide a more comprehensive picture of the technology industry's status.

How do companies reduce tech layoffs?

Layoffs in tech are hard – for the employee who is losing their job, the recruiter or HR professional who is tasked with informing them, and the company itself. So, how can we aim to avoid layoffs? Here are some ways to minimize resorting to letting people go:

Salary reductions

Instead of laying off employees, businesses can lower the salaries or wages of all employees. It can be accomplished by instituting compensation cuts or salary freezes.

Implementing a hiring freeze

Businesses can halt employing new personnel to cut costs. It can be a short-term solution until the company's financial situation improves.

Also, read: What Recruiters Can Focus On During A Tech Hiring Freeze

Non-essential expense reduction

Businesses might search for ways to cut or remove non-essential expenses such as travel, training, and office expenses.

Reducing working hours

Companies can reduce employee working hours to save money, such as implementing a four-day workweek or a shorter workday.

These options may not always be viable and may have their problems, but before laying off, a company owes it to its people to consider every other alternative, and formulate the best solution.

Tech layoffs to bleed into this year

While we do not know whether this trend will continue or subside during 2023, we do know one thing. We have to be prepared for a wave of layoffs that is still yet to hit. As of last month, Layoffs.fyi had already tracked 170+ companies conducting 55,970 layoffs in 2023.

So recruiters, let’s join arms, distribute those layoff lists like there’s no tomorrow, and help all those in need of a job! :)

Hiring Tools

What is Headhunting In Recruitment?: Types & 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.

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Developer Insights

Data visualization packages in R-Part I

Using dplyr and tidyr

tidyr Functions

gather()

spread()

separate() & unite()

dplyr Functions

select()

filter(), slice(), distinct(), sample_n(), sample_frac()

group_by() & summarise()

mutate()

Joins

arrange()

Data Visualization with ggplot2

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7 tech recruiting trends for 2024

Trend #1—Leverage data-driven recruiting

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Trend #4—Have a diversity and inclusion oriented company culture

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(Part 2) Essential Questions To Ask When Interviewing Developers In 2021

What constitutes a good interview question?

Hire GREAT developers by asking the right questions

#1 How do you plan your day?

#2 Do you have experience using tools for collaboration and remote work?

Value-based interview questions to ask

#3 Please describe three recent projects that you worked on. What were the most interesting and challenging parts?

#4 You’ve worked long and hard to deliver a complex feature for a client and they say it’s not what they asked for. How would you take it?

#5 What new programming languages or technologies have you learned recently?

#6 What does the perfect release look like? Who is involved and what is your role?

#7 Tell me about a time when you had to convince your lead to try a different approach?

#8 What have you done with all the extra hours during the pandemic?

(Part 1) Essential Questions To Ask When Recruiting Developers In 2021

Recruit GREAT developers by asking the right questions

#1 Write an algorithm for the following

#2 Formulate solutions for the below low-level design (LLD) questions

#3 Some high-level design (HLD) questions

#4 Have you ever worked with SQL? Write queries for a specific use case that requires multiple joins.

#5 What do you think is wrong with this code?

Best Pre-Employment Assessments: Optimizing Your Hiring Process for 2024

What is Pre-Employement Assessment?

Why pre-employment assessments are key in hiring

Improved decision-making:

Reduced bias:

Increased efficiency:

Enhanced candidate experience:

Types of pre-employment assessments

1. Skill Assessments:

2. Personality Assessments:

3. Cognitive Ability Tests:

4. Integrity Assessments:

Leading employment assessment tools and tests in 2024

HackerEarth:

SHL:

`gather()`

`spread()`

`separate()` & `unite()`

`select()`

`filter()`, `slice()`, `distinct()`, `sample_n()`, `sample_frac()`

`group_by()` & `summarise()`

`mutate()`

`arrange()`

What is Headhunting In Recruitment?: Types & How Does It Work?