Developer Insights

The benefits of honing technical skills go far beyond the Information Technology industry. Strong tech skills are essential in today’s changing world, and if your employees consistently and proactively enhance their IT skills, you will help them improve both personally and professionally. This, in turn, will help your business grow.

Yes, it may feel overwhelming. However, with the right attitude and flexibility of mind, it can also be a tremendous opportunity for your employees to learn and grow. Here are some of the hottest tech skills (a mix of programming languages, tools, and frameworks; in random order) to hire which will help you thrive in the workplace of tomorrow.

1. JavaScript

JavaScript has been the fastest-growing and the most sought-after programming language for years. It is considered as one of the smartest choices for building interactive web interfaces as all modern browsers support JavaScript.

Source: Twitter

The Stack Overflow developer survey results show that about 69.7% of 90,000 professional developers stated JavaScript is the most commonly used programming language. The same survey reveals that JavaScript is one of the most desired languages. This means that 17.8% of respondents have not yet used it but want to learn it.

The language is at the heart of several prominent tech companies, such as Netflix, PayPal, Groupon, LinkedIn, and Walmart. Additionally, studies reveal that JavaScript is among the most in-demand programming language used in the top privately-held startups valued at over $1 billion in the US. Hence, JavaScript will remain one of the hottest tech skills and it is unlikely that it will go off the grid in the near future.

Common job roles requiring JavaScript

Some of the common job roles requiring JavaScript as a skill are:

• Frontend web development
• Full-stack web development
• Information security software developers
• WordPress developers
• PHP and JS developers

2. Python

Released in 1991 and created by Guido van Rossum, Python was and is still extremely relevant for all developers to learn and grow. It is interactive, dynamic, versatile, and remains one of the most relevant languages.

Source: Coding Dojo

Also, it is one of the most popular programming languages used by the top 25 unicorn companies in the US.

It is an all-time favorite of beginners and experienced developers alike, mainly for its ease of use and simple syntax. Right from programming projects such as data mining and Machine Learning, Python is the most favored programming language.

Also, read The complete guide to hiring a Python developer.

Common job roles requiring Python

Some of the common job roles requiring Python as a skill are:

• Data scientists
• Data analyst
• Software engineer
• Machine Learning engineer
• Research analyst
• Python developer

3. Java

It is no surprise to see Java as one of the hottest tech skills. Introduced in 1991 by James Gosling, Mike Sheridan, and Patrick Naughton, it is a robust, general-purpose programming language that is object-oriented and class-based. It was designed in such a way that it is easy to use, write, compile, debug, and learn, and have as few implementation dependencies as possible.

Studies reveal that Java is one of the most popular programming languages used by developers.

This can be attributed to the fact that Java is widely used in industries such as financial services, Big Data, stock market, banking, retail, and Android. It is present everywhere! Whichever domain a developer works in, he/she will surely come across Java Programming.

An article by the Dev Community speaks about how Java is unarguably one of the most popular programming languages in the world today and how tech giants are using the language to build large portions of their infrastructure and backend services.

Also, read The complete guide to hiring a Java developer.

Common job roles requiring Java

Some of the common job roles requiring Java as a skill are:

• Java developers
• Java architects
• Backend developers
• Fullstack developers

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4. Rust

For the fourth year in a row, Rust has been voted as the most loved programming language in a StackOverflow report, followed by Python. This meant that more developers want to continue working with Rust than other languages.

Also, as shown by Google Trends, Rust has been gaining tremendous popularity over the years and its adoption is expected to grow.

Tech companies like Google, Amazon, and Microsoft have invested in Rust as a long term system programming language because it is expected to replace a lot of C and C++ development. In fact, PyPl has ranked Rust 18th in the Popularity of Programming Language Index, with an upward trend.

It makes a little more sense when you find out that the language was created at Mozilla, giving web developers a chance to write code that’s more performant than Ruby, PHP, JavaScript, or Python.

Common job roles requiring Rust

Some of the common jobs requiring Rust as a tech skill are:

• Backend developers
• Embedded system engineers
• Network engineers

5. ReactJS

Released in 2013, ReactJS is essentially a front-end library created by Facebook for building user interfaces. It serves as an excellent tool for the development of full-scale, dynamic applications.

As per a Stack Overflow report, ReactJS is the most wanted and most loved web framework.

A great performance benefit of ReactJS is its ability to update virtual DOM. As Virtual DOM is rendered from the server-side as well as the client-side, it offers a high-performance rendering of complex user interfaces. This is why ReactJS is fast. Other than Facebook and Instagram, ReactJS is adopted by the BBC, Netflix, and PayPal.

Common job roles requiring ReactJS

Some of the common job roles requiring ReactJS as a skill are:

• Frontend developers
• Full-stack developers

Looking to hire ReactJS developers? Identify top candidates with HackerEarth Assessments.

6. Docker

Docker is a tool that creates, deploys, and runs applications within containers.

Containers store up code and all its dependencies so that an application runs fast and reliably on any other Linux machine. The prevalence of Docker in the job market is incredible. In a Stack Overflow survey, developers ranked Docker number 2 in the “Most Loved Platform” category and number 1 in the “Most Wanted Platform” category.

With cloud and Docker becoming significantly linked every day, the demand is only expected to grow. Therefore, if your employees want a wonderful future in DevOps, they need to have a strong understanding of Docker tools.

Common job roles requiring Docker

Some of the common job roles requiring Docker as a skill are:

• Software developers
• Backend engineers
• DevOps engineers
• Python developers
• Site reliability engineers
• Database administrators

7. NumPy and Pandas

There would be no Data Science in Python without NumPy and Pandas (this is also one of the reasons why Python has become widely popular in Data Science.) As per GitHub, among the most popular public repositories labeled with topics like “Deep Learning,” “Natural Language Processing,” and “Machine Learning,” over half of them are built on NumPy. Pandas is a widely used tool, particularly in data munging and wrangling. It is available for everyone as an open-source, free-to-use project. Hence, NumPy and Pandas are expected to be in the race of tech skills to hire for.

Common job roles requiring NumPy and Pandas

Some of the common job roles requiring NumPy and Pandas as skills are:

• Data scientists
• Python developers
• Machine Learning developers
• Software engineers
• Algorithm developers
• Tech leads

8. Kotlin

Kotlin is a general-purpose programming language that effortlessly combines object-oriented and functional programming features within it. In a Stack Overflow report, Kotlin made its way into one of the most loved and most wanted programming languages.

Kotlin was designed to be interoperable with Java which makes Android development faster and enjoyable. Also, Kotlin addresses the major issues that surface in Java. Hence, several Java apps are rewritten in Kotlin. Brands like Pinterest and Coursera have already moved to Kotlin due to its strong tooling support. It receives a lot of interest from developers and companies alike. The job postings for Kotlin increased over 15X, from the second quarter of 2016 to the second quarter of 2018, and the trend is only expected to grow.

Source: Dice

Hence, Kotlin is a hot tech skill that programmers and Android app developers should learn.

Common job roles requiring Kotlin

Some of the common job roles requiring Kotlin as a skill are:

• Android developers (junior, mid, senior)
• Kotlin developers
• Software engineers—Android platform

9. Django

Django is one of the most versatile and popular Python web frameworks that encourages rapid development and pragmatic, clean design of web applications. This can be attributed to Django’s open-source nature—the community is constantly releasing new code and plug-ins to simplify the process and keep up with the demand. It grabbed eyeballs right from the start when it was positioned as Python’s answer to Rails.

Many Python development services, as well as major companies such as Spotify and YouTube, use Django. Developers describe it as “batteries included”, which means that it comes with a variety of third-party libraries.

Django’s user base is expected to grow as more developers embrace Python for emerging technologies such as Machine Learning and Big Data. It is ridiculously fast, reassuringly secure, and exceedingly scalable.

Note: We recommend using the latest version of Django, which is currently 3.0.2.

Common job roles requiring Django

Some of the common job roles requiring Django as a skill are:

• Python-Django developers
• Python software engineers
• Full-stack Django developers
• DevOps engineers
• Frontend Django developers
• Django software engineers

Summing up…

All developers have a thirst for learning new skills. However, knowing which skills are gaining popularity can ensure better career growth and help developers prioritize learning them first. Recruiters and developers can use the information shared in this post to make informed decisions in this matter.

As a recruiter, you need to keep yourself abreast of the above-mentioned skills to stay ahead of your competitors in hiring stellar talent.

Not sure about how to assess technical skills? HackerEarth provides accurate technical screening and helps you hire the best. Start your 14-day free trial today.

System design can be a huge leap forward in your career both in terms of money and satisfaction you get from your job. But if your previous job was focused on working closely on one of the components of a system, it can be hard to switch to high-level thinking

Imagine switching from roofing to architectural design. Instead of knowing the ins and outs of making one component, you need to develop a system of components that work well together. This is why so many people fail in system design interviews. They don’t understand what the interviewer wants to hear from them.

What are interviewers looking for?

You walk into an interview, ready to discuss the pros and cons of using NoSQL, fine details of implementing map-reduce, and the possibilities of using the newest node library. What do they ask you? Design Netflix from scratch.

This leaves many interviewees puzzled, and they do two crucial mistakes. The first mistake is focusing too much on the service that already exists. The interviewer doesn’t want to know how Netflix or Twitter is actually made. Rather, they want to see your thought process that goes into creating a similar system.

The second mistake is focusing too much on details. That’s not what you need to do, at least not at first. The technical knowledge and the ability to solve bottlenecks is great, but your main goal for such interviews should be understanding the type of system you need to develop and figuring out the optimal way of solving user problems.

How to ace a system design interview: A step by step guide

Now that you know the direction, let’s go through the interview, step by step.

Step 0: Get good

Preparing for the interview starts months before you arrive at the office. You need to work on gaining knowledge and acquiring skills to be sure that you have what it takes to crack it.

This includes a lot of reading. Start with following high scalability and getting yourself a copy of Martin Klepmann’s Designing Data-Intensive Applications. It’s a great place to start if you have limited experience with system designs.

If you have the knowledge but struggle to apply it to real-world problems, try hosting brainstorming sessions with your pals. After all, trying to design Twitter from scratch can be fun when your employment doesn’t rely on it.

You can go even further and attend a hackathon to try implementing your system design knowledge in practice and get expert advice on it. When you feel confident about your skills, start polishing them before the interview. For instance, you can focus your practice on the typical cases interviewers offer.

In most cases, the interviewer will ask you to design one of the following services:

• URL shortener
• Social network
• Messenger
• Video streaming
• File storage
• Search engine

If you know a bit about each of these services, you’re already on the right track. To gain even more confidence before the actual interview, attend a mock one. You can do it online, and instead of “we’ll call you back”, you’ll receive an expert opinion on your performance.

Step 1: Define the key assumptions about the system

Now, let’s say you’ve made it to the interview. Given the number of applications big tech companies receive, it’s already an achievement. You feel good about yourself, and when the interviewer asks you to develop something like Facebook, you start talking about peculiarities of data storage and what is the best way to create a dynamic feed.

That’s not what they expect to hear. First, you need to understand what kind of system are you building. What is the intended audience? What problems are they solving with this service? You’ll need to answer those questions before you can go any further.

In many cases, the interviewer won’t know the answer. Why? Here’s a very important thing about system design interviews: it’s not about giving the correct answer to a well-defined problem, but it’s about your ability to define the open-ended problem and solve it creatively.

This means you can pretty much decide on these key assumptions together with the interviewer.

Step 2: Define the key features

Once that is out of the way, your next step is defining what kind of features your hypothetical service must possess. Even though your task is designing an already existing service from scratch, it doesn’t mean they should be identical.

For instance, if you’re tasked with designing Facebook, you can take the features this social media has as the basis and work from that. Think of ways you can combine Messenger and Facebook into one app instead of two or suggest how to make ads more user-friendly.

If you’re tasked with developing a Discord-like chat, you’ll need to include secure chat rooms with stable voice chat features. You can also suggest a streaming option. If you need to develop a digital product marketplace such as Pro Essay Writer, you’ll need to combine features like dynamic display of offers, secure access to database, and several payment options. You can throw in a Ai live chat or a monitoring feature to make sure the freelancer the user has hired is busy working on the project.

This will show the interviewers that you’re not only capable of reverse-engineering a service, but actually thinking about the problems customers face and solving them.

Step 3: Define the scale

While the system you design should be scalable, you need to start somewhere. This is why you need to define the scale of the system at first. Think about the read-to-write ratio, the number of concurrent requests the system should expect, and various data limitations.

Once you define these parameters together with your interviewer, you can think of the best way to make that system work well and be scalable. But before that, there’s one more step.

Step 4: Define the data model

Before you can design the hypothetical system, you need to define how you’re going to process data. Find out the main inputs and outputs, how they’re going to be stored, and how the data will flow.

This doesn’t require you to know every little aspect of implementing MongoDB or the latest MySQL library. If you know what database would serve the purpose better, it’s going to be enough. Remember, you don’t need to go into detail too much at this stage.

Step 5: Design the high-level system

By this time, you should have all the information necessary to design the system your interviewer wants. Ideally, you should be no more than 15-20 minutes into the interview.

Start with the entry-points and work your way up to the database. If the interview room has a whiteboard, it’s a great opportunity to visualize your ideas, but even a sheet of paper will do. Draw the architecture that’s needed to support all user and API interactions and present a decent response time.

Don’t be afraid to change the layout of the system on the go. Interviewers don’t care about you making mistakes. They want to see if you’re able to iterate your ideas and improve as you go along.

Step 6: Look for bottlenecks

Once your version of the system seems more or less final, you can get down to details. Look for possible bottlenecks that can slow down or hinder the functions of the system. It’s also okay to take the interviewer’s advice on this. In many cases, the interviewer is an expert on the topic, so you’ll only show your readiness to learn and improve by this.

Find out the bottlenecks and come up with ways of eliminating them either by redesigning a part of the system, or scaling up the hardware.

Step 7: Go in-depth on the subsystem you know well

This is an optional step, but many interviewers ask you to go through this as well. You’ll have to go low-level and elaborate on a subsystem. If you can, steer the conversation to the one you know best.

There’s no shame in admitting you don’t know much about a certain subsystem. After all, you’re no Renaissance man, and the company you’re applying to has teams of experts working on each subsystem, so you’ll have plenty of opportunities to consult with them.

Show off the knowledge you have, and move to the next step.

Step 8: Acknowledge the trade-offs

No system is ideal, and a good system design engineer knows that well. Let the interviewer understand what trade-offs did you make to let the system work well at this stage.

Stay in touch

With that, your 45-minute interview should be over, and the interviewer would be either impressed or bored with your take on the problem. Regardless, you should try to stay in touch with them to increase your chances of getting hired. At the very least, you may get an expert opinion on what went wrong.

If you’ve failed the interview, don’t stop in your tracks. It’s just an opportunity to learn more and practice more. Join Hackathons and do mock interviews to up your skills, and you’ll get the job you’ve been dreaming about.

This blog is a guest contribution from Harsh Goel, Founder@ InterviewCamp.io – Online Bootcamp for Technical Interviews

Machine Learning or Blockchain might be the next big thing, but interview problem-solving is the skill of the decade.

Here is a step-by-step plan to improve your data structure and algorithm skills:

Step 1: Understand Depth vs. Breadth

We all have that friend who has solved 500 coding problems. They love to wear it as a badge of honor. But when it comes to interviews, they fail miserably. This is a very common scenario. It’s what we call the “Breadth-Only” approach. They are solely focused on solving as many problems as they can.

The Breadth-Only approach has a problem—you don’t build a strong foundation. Interviews require deep problem-solving knowledge and the ability to code fast and accurately. You only develop these skills with focused preparation.

Here’s a counter-intuitive approach that works better:

Focus on less problems, not more

This is comforting, right? Who wants to focus on 500 problems when you can focus on 100?

But here’s the key—you want to learn them in depth. This is where depth comes in.

When you analyze a problem in depth, it means:

1. You can code it quickly
2. You can code it with correct syntax, which means you are good at the language
3. You can write clean code in one go, because it’s second nature to you
4. You can apply the same code to a new problem quickly
5. You know the data structure you are using and can implement it if asked to

To achieve this, you need to focus on a few representative problems (around 100 works well.) Solve them a few times and you’ll start seeing patterns. You also start getting better at the coding part.

So you’ve covered Depth, congratulations! You have acquired a solid base.

You can now go all out and solve as many problems as you want. And best of all, you won’t need to code many of them. Figure out a solution, and if it’s similar to one of your core problems (which it often is), you’re done. No need to actually code and debug it because you’re already good at that.

Step 2: Start the Depth-First Approach—make a list of core questions

Identify a list of ~100 core problems. Many sites give you 100 curated problems.

Here’s another way:

Get these two books:

1. Elements of Programming Interviews
2. Cracking the Coding Interview.

Collectively, they give you a good variety of hand-picked problems. If you want a structured course for this, check out InterviewCamp.io

Step 3: Master each data structure.

Now that you have finalized your list, start with the basics. Know every data structure.

Learn how to use each data structure in your language.

Also, learn how to implement them. Yes, implement them by hand. Many people ignore this, but it’s extremely important. Interviewers can ask you about data structure internals. Many problems modify data structures or re-engineer them for a specific use case. To utilize them fully, you need to know how they work.

For example:

Interviewer: “So you initialized an array-backed list. Good. Now let’s say you reach its capacity, what happens when you try to add another element?”

Candidate: *blank* “What do you mean capacity? I can keep adding elements to this list.”

Interviewer: *facepalm*

In this case, the candidate had been using Python, and there’s no concept of list capacity. You just keep adding elements. But that’s not what happens under the hood. You need to know what data structures back a list, and how that works.

Here’s another example:

Let’s say you’re asked to Implement a Queue using just Stacks (a popular question). This is a modified data structure. If you haven’t implemented either of those before, you’ll have trouble getting started.

Now, this doesn’t mean you need to know every implementation’s code. Some data structures are pretty hard to implement – for example, deleting a node from a Binary Search Tree is not trivial to code. But you should know how it works.

webflow.hackerearth.com/blog/leadership-personality-behaviors

Further Reading

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Here is a list of data structures to master :

• Arrays and Lists
• 2D Arrays
• Strings
• Linked List
• Stack
• Queue
• Hash Table & Hash Set
• Heap
• Graphs
• Binary Tree
• Binary Search Tree
• Trie

How to go about it? Let’s say your core problems are divided by data structure. You can master each data structure when you start each section. Or, you can master them all at the beginning. Do what works for you.

(Check HackerEarth Data Structure & Algorithm practice)

Step 4: Spaced Repetition

Alright. You made a list of questions and you started solving them. Here’s a common question we get:

“I solve many questions but can’t solve them a week later! How do I remember solutions?”

The key is to not remember solutions. The key is to practice them. When you see a problem, you should immediately be able to break it down and re-create the solution. This is different from rote learning. You’re recognizing different components, breaking them down and solving the problem.

The best technique we’ve seen – solve the problem again in 3 days. Then in a week. Then in a month. It will become second nature to you.

Step 5: Isolate techniques that are reused. Isolate actual code blocks.

This is where the Depth-First approach gets exciting. As you solve these problems, you’ll start to notice patterns.

Let’s say you solved 5 problems that used Binary Search. You can isolate the Binary Search code and practice it over and over. You know it will be used in similar problems.

And this is one of many techniques you can isolate. Here are some other common ones:

• Depth First Search
• Recursion + Memoization
• Hash Table + Linked List combination
• Searching a Binary Tree etc.

Now, you have a collection of techniques you can apply to new problems.

Step 6: Now, it’s time for Breadth.

Let’s say you’ve mastered your core problems. Using common data structures is second nature to you. You can now look beyond your core set. Because you’ve implemented so many techniques already, you don’t even have to code all the new questions.

During this time, try to solve realistic interview problems. Once you get good, there’s a tendency to focus on really hard problems. The thought process is – “if I can solve these really hard problems, then interview problems will be a piece of cake!”. That’s not usually the case. Techniques in really hard problems often have nothing to do with interview-level problems.

Step 7: Practice on paper

We recommend practicing on paper at some point in your prep. When you code without an IDE and Stack Overflow, it takes you away from your comfort zone.

Here are some benefits of practicing on paper:

1. You’re forced to plan your code before writing. You can’t just go back and retype.
2. You will start learning correct language syntax and data structure usage. With an IDE, code used to write itself.
3. You can take a paper and pen anywhere with you to practice.

And more importantly, it is a realistic simulation of a whiteboard interview.

Congratulations, you’re now a pro! Let’s get those interviews rolling.

Also read – Top 7 algorithms and data structures every programmer should know about

Technology has evolved drastically over the last decade and is only expected to continue transforming.

With the changing landscape, the skill sets that organizations look for in tech professionals is also changing. A survey of 42,300 employers across 43 countries and territories found that the demand for IT skills has skyrocketed.

However, it is a known fact that there are more jobs than candidates in the IT industry.

At HackerEarth, we have helped thousands of organizations find top tech talent. Based on our analysis, here are the four hardest tech roles to fill and tips on how recruiters can find the talent that their firm needs.

Software architects

The unicorns of the tech job market, software architects make high-level design choices and define software coding standards. According to research, the Software Architect role has one of the highest talent deficits.

It’s likely because this job requires a plethora of skills such as strong communication to interact with clients, reviewing code, mentoring when required, a high level of foresight and vision, and more.

Software architects define the success or failure of a project and set standards for future developers to follow.

The solution

Here are a few tips you can follow while hiring a software architect.

• Know the difference between a software developer and a software architect

To hire a software architect, it is crucial for recruiters to have a clear understanding of the difference between a software developer and a software architect. The primary difference is that a software architect is a software expert and is responsible for defining the bigger picture. His/her main role is to understand how a product that is being built will ultimately help the customer.

Some of the key differences between a software architect and a software developer

• Know where to find them

There are a handful of go-to online communities where software architects learn and share information such as Meetup, IBM Community, Code Project, and Stack Overflow.

• Know how to interview them

While looking for a software architect, it is obvious that you will evaluate the technical competencies of the candidate. However, only assessing the technical skills of a candidate does not assure a quality hire. Here’s an approach that you could follow:

1. Ask candidates to describe a system that they have designed—a system that they are proud of or one that they have worked on recently.
2. Although many engineers dislike whiteboard interviews, it is the holy grail of software architects. After all, they can draw, discuss, and explain their technical diagrams and system designs better on a whiteboard.
   While candidates take the test on a whiteboard, notice their body language—are they relaxed while explaining the system? Are they excited while explaining the system? Is their excitement contagious? If the answer is yes to all of the questions stated above, you have probably got yourself a great, potential hire.
3. Good software architects can make complex subjects sound simple. Whether one is tech-savvy or not, a good software architect should be able to clearly describe a system to anybody.

• Know what skill sets to look for

While hiring a software architect, ensure that he/she is proficient in the following skill sets:

1. Technical knowledge
2. Management skills
3. Communicability
4. Analytical skills
5. Ability to identify business requirements
6. Code review
7. Architectural review
8. Writing project documentation and its support
9. Creating unified development standards in the company

Hire your next software architect

Data Scientists

Data scientists are analytical professionals who make effective use of large and unstructured data and create insights from it. A lot of highly skilled people geek out to solve complex Data Science problems.

A data scientist’s job is often considered one of the most in-demand jobs of the 21st century. Adding to it is the attractive salary that comes with being a data scientist. However, the 2019 State of the CIO report reveals that a data scientist is one of the most difficult tech roles to fill.

The reason is undoubtedly justified: it is a competitive job market. According to First Round, an ideal Data Science candidate often receives 3 or more job offers.

Hence, the success rate of hiring is commonly below 50%. As the number of businesses in the Data Science niche is continuously growing, top candidates have more job opportunities to choose from. Hence, finding and hiring qualified candidates is now even more difficult for recruiters.

The solution

You can consider doing the following to get a great data scientist on board.

• Focus on developer branding
• The only way to stand apart in a pool of similar businesses is to build a great solid developer brand that attracts top talent. One great way to hire amazing data scientists is to show them that developers love working for your brand.
• To build a strong developer brand, you should follow practices such as setting up live sessions on ‘Why we are the #1 brand for developer talent?’ (an example), use your network to build a talent pipeline, understand brand perception, etc.
  Read more about developer branding here.
• Perfect your Data Science candidate experience
• Research reveals that organizations that invest in a strong candidate experience improve their quality of hires by 70%.
  One good practice to follow is to provide Data Science candidates with a comfortable coding environment to ensure a seamless candidate experience.
• For example, while assessing Data Science candidates, HackerEarth provides a coding interface that allows you to assess a candidate’s Data Science (data analytics and Machine Learning) skills.
• The solution submitted by candidates is evaluated based on the accuracy of predictions on ‘Sample’ or ‘Public’ data for compilation. The score is revised on the ‘Full’ or ‘Private’ data when candidates ‘Submit’, thereby preventing the candidates from over fitting their model.
• Look at online communities
• Tech communities are full of potential hires waiting to be discovered. To source potential data scientists, look at online communities such as Data Quest, KaggleNoobs, Data Scientists, Data Science Salon, and more. These communities can help you connect with a worldwide resource of data scientists.
• Do your research
• Research the skill sets to look for in a candidate when hiring for a data scientist. An ideal data science candidate will have skills in the following areas:
• 1. Programming languages (specifically Python or Java)
• 2. Strong analytical skills
  3. Strong mathematical skills
• This blog provides in-depth information about what Data Science is and how to hire a data scientist.

Hire your next data scientist

Cybersecurity professionals

Companies are facing security breaches at an alarming rate, putting every web user’s data at risk. The Heartbleed Bug is a recent example highlighting the need for cybersecurity professionals.

Cybersecurity professionals are trained to find loopholes in databases, networks, hardware, firewalls, and encryption. Their number one priority is to prevent attacks by ‘fixing’ potential issues before they are exploited by malicious users.

Additionally, cybersecurity specialists handle the clean up after cyber attacks and security breaches.

However, research reveals that there is now a gap of almost 3 million cybersecurity jobs globally.

The solution

To tackle the crunch for cybersecurity talent, here are a few best practices that can help you recruit the best cybersecurity talent.

• Conduct hiring drives in universities that offer cybersecurity courses
• Today, several universities across the globe offer specializations in cybersecurity. A few examples of these courses include network security, information security, cyber investigation, cybersecurity management and policy, and others. Organizations can conduct campus hiring drives to get fresh cybersecurity graduates on board.
• Train your current employees in-house
• Offer cybersecurity certification courses to your current employees. In the talent-strapped industry of cybersecurity, this approach will not only help employees develop their skills and advance their career progression, but it will also provide an alternative to external hiring.
• You can also consider bringing in external experts and consultants for training processes. Although this can be a costly business, it may well work out cheaper than starting the hiring process from scratch.
• Be flexible with job requirements
• To land a job as a cybersecurity professional, most candidates require a Certified Information Systems Security Professional (CISSP) certificate. However, to obtain this certification, it requires one to have a minimum of five years of industrial experience.
• Such requirements, such as a particular certification or degree, or a certain number of years of experience, eliminate talented individuals before they even have a chance of demonstrating their skills.
• While candidates with this certification may be more qualified than those without, it may not be necessary for every position in cybersecurity, particularly entry-level roles.
• Look for must-have cybersecurity skills
• 1. Intrusion detection
  2. Malware analysis and reversing
  3. Programming knowledge
  4. Risk analysis and mitigation
  5. Cloud security
  6. Security analysis

Hire your next cybersecurity professional

Engineering Managers

Engineering managers are responsible for supervising other engineers and projects, hiring staff, setting budgets, spurring new development, and solving problems in an organization.

An ideal engineering manager leads research and development of projects and checks the accuracy of the work produced under his/her supervision.

Overall, they are expected to troubleshoot roadblocks throughout any project and solve problems that may act as hindrances in project completion.

With such varied roles and responsibilities, it is but obvious that engineering managers are hard to find. More complex the role means a longer time-to-hire. In fact, some say that good engineering managers are not just hard to find, they don’t exist.

The solution

We have listed down a few solutions (positive outcome guaranteed) on how to find and hire an engineering manager.

• Look for engineering management forums

There are various forums such as engineering.com, ProjectManagement.com, management societies, and in-person events to help you understand where your ideal candidates are spending their time.

• Understand the biggest challenges they face and work on resolving them

An engineering manager is someone who has good technical as well as people management skills. Hence, understanding the nuances of the role can set your recruitment team apart from the competition to hire an engineering manager.

Some of the challenges that engineering managers face motivating unmotivated team members, reading more and writing less code (this can be a shock for anyone who loves programming), showing empathy while driving business initiatives, etc.

• Skills to look for in an engineering manager

Some of the must-have skills for engineering managers are:

1. Up-to-date knowledge of software technologies
2. Excellent ability to read code
3. Management skills
4. Deep understanding of an organization’s process, vision, and products

We believe a knowledge of the basics we have outlined here will help you gain a deeper understanding of how to fill these critical roles in your organization.

Hire your next engineering manager

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