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Getting started with Machine Learning

Have you ever understood the process of learning? How you learn how to perform a particular task? How do you learn to play a musical instrument? How do you learn social convention? How do you learn to lie? Apart from humans, plants and animals possess the ability to learn. And in recent times, so have machines.

Today machine learning is responsible for everything from Siri, Google Now, the recommendation engine on YouTube and Netflix, to even the driverless cars. Surely, machine learning is something that every computer scientist will encounter sooner or later, and it is important to learn this well.

History of Machine Learning

Machine learning was the byproduct of the early endeavours to develop artificial intelligence. The aim was to make a machine learn via data. But the use of this approach often resulted in reinventing already existing statistical models. This, coupled with the increase in knowledge and logical based approach to AI put machine learning out of favour among the AI community. Machine learning soon became a sub-sect of statistics and data mining.

But, over time, Machine Learning has become a separate field of its own. Instead of striving to achieve artificial intelligence, the main aim of machine learning has become more towards tackling solvable problems. It borrows techniques from statistics and probability to focus on predictions derived from data.

Machine Learning and AI

Ever since the rebirth of machine learning as its own field, there has been many a debate on the distinction between machine learning and AI.

There is one group that believes that machine learning is the only kind of AI there is. As machine learning enables a machine to learn based on external stimuli, it is in essence mapping the mind, which makes it the only kind of AI there is.

There are those who also believe that while machine learning is AI, AI is more than just machine learning. AI includes concepts like symbolic logic, evolutionary algorithms and Bayesian statistics and many other concepts that don’t fall under the purview of machine learning.

The important thing to note is the goals that each one of them try to achieve. Apart from machine learning, AI tries to achieve a broad range of goals like Reasoning, Knowledge representation, Automated planning and scheduling, Natural language processing, Computer vision, Robotics and General intelligence. Machine learning on the other hand focuses on solving tangible, domain specific problems through data and self learning algorithms.

So what are the skills you need to learn to get started with machine learning? Read on -

Seeing Is Believing

R2D3 has one of the best visual representations of what machine learning is. It takes the example of room sizes and elevations of homes in different cities in the US. This visual representation is a walkthrough of the techniques used to build an algorithm that will be able to predict the location of the house based on the dimensions of the rooms. Check out R2D3.

Another great resource is this blog on the Scikit learn site. In fact, at some point you will use Scikit learn, which is an open source machine learning library for the Python programming language.

Kaggle is one of the sites known for machine learning contests. This guide is a great starting point for anyone with a little bit of programming skills.

The Tongue

While most programmers prefer Python for its all-round capabilities and its data exploration prowess. However, the kind of programming language that you need to use depends on the machine learning application. This answer on Quora by a former Googler beautifully elucidated the process behind choosing a language while building your machine learning algorithm. Apart from Python, languages like C++, R and Java are popular among machine learning enthusiasts.

There are many libraries in Python for machine learning. Pybrain is one of them. As mentioned before, Scikit learn is another popular machine learning library in Python.

Key Skills

The language is only one of the many skills that you need to be adept at machine learning. You will need sound understanding of probability and statistics, applied mathematics and algorithms, distributed computing, big data and even signal processing techniques. Joseph Misiti, a data scientist at Square, explains the intricacies of each of these requisites.

This blog post on Udacity by a data scientist at Airbnb is a great post on the skills that a data scientist in today’s age is expected to have.

CMU has a free and open course on statistics for machine learning, with video lectures, assignments and solutions as well.

The Attitude

And lastly, and perhaps the most important trait that someone pursuing machine learning needs, is the attitude of a data scientist. This article from the Zipfian Academy elucidates the mindset that a good data scientist needs and this mindset goes a long way in being good with machine learning as well.

While you’re at it, you should also check out the machine learning track at IndiaHacks. It’s a fantastic opportunity to get your hands dirty with a real time machine learning problem and put yourself to test with some of the best talents in the machine learning space.

Top skills a full stack developer should have

Who is a Full Stack Developer?

A good full stack developer is like a celebrity who can do it all—act, sing, DJ, host, direct, and produce. While they may not win an Oscar or Grammy, they bring versatility and breadth of experience to the table.

They are capable of building complete applications—web, mobile, or desktop. They understand both front-end and back-end development, and are familiar with servers, databases, APIs, MVC architecture, and hosting environments. (Top skills a full stack developer should have)

Full stack web application layers

Full stack developers are in high demand with thousands of openings on job platforms. However, they may not always be the right choice for every scenario.

When to Hire a Full Stack Developer

  1. When You Need an MVP

    For startups or lean operations aiming to validate ideas with a minimum viable product, full stack developers are ideal. They can convert concepts into functional prototypes efficiently.

  2. When You Need Product Managers

    With their technical and business understanding, full stack developers often make great product managers who can balance both sides effectively.

  3. When Cost Is a Constraint

    If hiring specialists for every layer isn't viable, a full stack developer can provide excellent value. One skilled developer may cost less than hiring three specialists. (Recruit on a shoestring budget)

  4. When You Need a CTO/Co-Founder

    Full stack developers make excellent co-founders or CTOs, especially for those seeking a partner to bring a technical idea to life. (More on CTO as a service)

When Not to Hire a Full Stack Developer

Do not hire a full stack developer if there is no clear value-add. At a large scale, specialized teams for each layer—data, infrastructure, front-end, etc.—are more effective than one generalist.

How to Hire a Full Stack Developer

Qualities to Look For

  • Passion for continuous learning
  • Broad understanding of various technologies
  • Problem-solving mindset, even if not hands-on
  • Stays updated with tech trends
  • Understands the business vision and user needs

Technical Skills

For web app development, a full stack developer should know:

  • HTML, CSS, JavaScript
  • Back-end programming languages
  • Databases
  • Version control (e.g., Git)
  • Deployment and hosting
  • Third-party APIs/services

More on required skills: Top skills for full stack developers

Resume Insights

Don't rely solely on resumes for technical evaluation. Look for:

  • Open-source contributions
  • Varied tech exposure
  • Real-world project experience

Alternative sourcing platforms like GitHub are often more insightful.

Technical Assessment

A real-life project is a better assessment than algorithmic tests. Use practical business problems to evaluate full stack skills effectively.

Sample real-life assessment problem

Interview Focus Areas

  • Ability to deal with uncertainty
  • Curiosity and eagerness to learn

Present unfamiliar problems and observe how candidates approach solutions—not just the outcome.

Hiring Tips Summary

  • Look for inherent developer traits
  • Make technical evaluations mandatory
  • Use appropriate methods to test technical knowledge

Use tools like HackerEarth Assessments to streamline the hiring process.

Popular Posts Like This:

  1. How to Hire a Data Scientist
  2. The Complete Guide to Hiring a Data Scientist
  3. 8 Ways to Hire a Developer

Subscribe to the HackerEarth blog and receive free monthly articles on tech recruiting and development straight to your inbox.

Dr. A. P. J. Abdul Kalam - One of India's best engineering managers

It is said that "A man is defined by the work he does". If we are to go by this saying, then Dr. A. P. J. Abdul Kalam, ex President of India, has left us with a lot of remember him by.

Even at the age of 83, Dr. A. P. J. Abdul Kalam involved himself in some of the most important ballistics work in the country. The most note-worthy being his contributions to cardiac technology-a stent that made heart surgeries affordable. And this is not even considering the amount of time that he had spent in sharing his knowledge with the world and philanthropic work he had done.

Here’s a chronicle of the great man’s illustrious life, through his work -

A glipmse of Dr. APJ Abdul Kalam's Life (15 October 1931 - 27 July 2015)

What struck me when this image was made out, is that after his first tenures in ADE and DRDO, his major contributions came through the mantle of being a leader. And while his accolade for being India’s missile man is fully justified, we often forget that he was probably India’s best engineering manager.



An astute engineer
"An engineering manager is someone who is entrusted with the job of synergising and aligning a team’s energies and talents to one common goal."

One must not only have a strong engineering foundation and subject expertise in the field of the project , but must also be a leader to be a good Engineering Manager.

In his early days, he was in a team that designed a light weight helicopter for the army. Apart from this, he also worked directly under Vikram Sarabhai, the founder of the Indian Space Research Organization, under whom he was a project director of the Rohini satellite program. While putting his engineering abilities to good use, he was also learning leadership from some of the best leaders in the world. In his own words, Kalam said,
“I learnt leadership from three great teachers—Dr. Vikram Sarabhai , Prof Satish Dhawan and Dr. Brahm Prakash. This was the time of learning and acquisition of knowledge for me.”

A business statesman

Post his tenure as a scientist, Dr. Kalam started to take up more leadership and management roles. Since Rohini, some of Dr. Kalam’s greatest contributions have come through his leadership roles in PSLV and SLV III. From here on, he led the design and development of India’s most potent missiles - Agni and Prithvi. Cumulatively, Kalam would have easily managed billions of dollars and thousands talented scientists and engineers.

A lot of any managerial job involves mentorship, and Kalam possibility embodies the quintessential mentor. Even his last moments were spent, trying to impart his knowledge with students, whom he loved spending time with. In fact, post his tenure of Chief Scientific Advisor to the Prime Minister, he set himself a target of interacting with at least 100,000 students, so he could share his knowledge and inspire more young people to take up science and technology. Surely a lot of this would have rubbed off on his subordinates too.

A leader

In my opinion, every leader is different. In Dr. Kalam’s case, he was a rare blend of brilliance, determination, foresight and humility. To start with, he was a brilliant scientist, who earned his stripes with some of the brightest minds in the world. That is the foremost requirement for an engineering manager. This earns an intellectual’s respect.

Secondly, a leader is not worried about rolling up his sleeves and getting work done. Kalam was as hard working as anyone else, and there are many employee accounts of his tremendous work ethic.

Examples of foresight are abundant in his book India 2020, where he very clearly describes what India needs to do to become a world superpower -
“I have identified five areas where India has a core competence for integrated action: (1) agriculture and food processing; (2) education and healthcare; (3) information and communication technology; (4) infrastructure, reliable and quality electric power, surface transport and infrastructure for all parts of the country; and (5) self-reliance in critical technologies. These five areas are closely inter-related and if advanced in a coordinated way, will lead to food, economic and national security.”

The ultimate engineering manager

All the professional characteristics that Dr. Kalam possessed are all the necessary ingredients for an astute engineering manager. However it was Kalam’s demeanor which really set him apart. In a world where the powerful is often come across as arrogant and brash, here was a man, with unsurmountable achievements in his kitty, who was as humble and down to earth as anyone could be.

It seeped through in his style of leadership. Popular journalist Rajdeep Sardesai recounts an interesting experience with him -
“In 2007, at the Ramnath Goenka journalism awards, I had the privilege of receiving the award from President Kalam. When a question and answer session followed the award ceremony, Kalam refused to sit in the front row. Instead, he came and sat cross-legged on the stage, asking us why we didn't focus more on science and technology in the news. It was a bizarre scene: pompous editors sitting on chairs while the easy-going president was on the stage floor asking us questions! This was quintessential Kalam: unconventional in style, be it his floppy silvery mane of hair, or inviting an audience to send him questions to his personal email: ‘please write to abdulkalam@apj.com, shall I repeat!’”

The engineering manager is the custodians of the engineering culture in any organization, and with the engineering fraternity needs a Kalam Blueprint for engineering managers.

CodeMonk: Our story

The Internet has a plethora of learning resources for anyone who wants to become a better programmer. However, there is no single place where one can find information and practice on the topics required to master the art of competitive programming. This is one of the reasons why many programmers in the pursuit of learning competitive programming attain a level of saturation after a while.

The difficulty that is faced in consuming content from varied sources led us to start Code Monk—a weekly series of tutorials on all the topics of computer science. The topics start from the basics of algorithms and gradually move on to more complicated concepts. Each tutorial is followed by a short programming challenge to help you test your understanding of the concepts.

This series aims to help you take your programming skills to the next level. We will provide you with learning content and room for practicing under one common platform. While the series focuses on aspiring programmers, experts can also use it to revise their concepts and improve their programming karma.After you signup, you will receive a link to the tutorials on the weekly topics every Thursday. A practice challenge will be conducted on the subsequent Wednesday on the same topic. All the problems from the challenges will be updated with proper editorials for your reference.The current schedule is as follows:
  • Week 1: Arrays & Strings (Completed)
  • Week 2: Sorting (Completed) and Searching (Completed)
  • Week 3: Stacks and Queues (Completed) and Number Theory - Part I (Completed)
  • Week 4: C++ STL (Completed)
  • Week 5: Graph Theory - Part I (2nd July)
  • Week 6: Hashing(8th July)
  • Week 7: Union Find Data Structure (15th July)
  • Week 8: Heaps, Priority Queue (22nd July)
  • Week 9: Minimum Spanning Trees (29th July)
  • Week 10: Greedy Technique (5th August)
  • Week 11: Dynamic Programming-Easy (12th August)
  • Week 12: Bit Manipulation (19th August)
  • Week 13: Computational Geometry (26th August)
  • Week 14: Binary Tree, Binary Search Tree (2nd September)
  • Week 15: Graph Theory - Part II (9th September)
  • Week 16: Number Theory Part II (PnC,Probability) (16th September)
  • Week 17: Segment Tree , RMQ, Lazy Propagation (23rd September)
  • Week 18: Binary Indexed Tree (30th September)
  • Week 19: String Algorithms (7th October)
  • Week 20: Number Theory - Part III (14th October)
  • Week 21: Tries,Suffix Tree (21st October)
  • Week 22: Suffix Array (28th October)
  • Week 23: Dynamic Programming Part II (4th November)
  • Week 24 and later: Will be published...
There will be a common leaderboard for the complete series along with individual leaderboards for every challenge. The top 3 participants will receive t-shirts. The focus of this series is to encourage beginners and our team will manually curate the list of winners based on their profiles.So, what are you waiting for? Start mastering the art of programming through learning and practicing today!

Update (10/12)

We have a new and improved version of CodeMonk. Read all about the changes in V2.0 this version here.

[Repost] The very brief history of Computer Science

I believe it is fundamental to have an overview of the history that later formed Computer Science. People know work of individuals such as Dijkstra. But there are so many others who've made valuable contributions to make computers we have today happen. It was a process that started in the early 800s and started to grow in the 1800s and the 1900s.

How did simple changes in voltage lead to the development of machines such as computers? Perhaps, we can attribute it to some incredible work by individuals from across different centuries.

Let's look at a few concepts these "greats" came up with during this amazing journey.

300 BC

In 300 BC Euclid wrote a series of 13 books called Elements. The definitions, theorems, and proofs covered in the books became a model for formal reasoning. Elements was instrumental in the development of logic and modern science. It is the first documented work in mathematics that used a series of numbered chunks to break down the solution to a problem.



300 BC — 800 AC

Following Euclid, notes about recipes, etc. were the closest thing to algorithms today. Also, there were inventions of mathematical methods. Sieve of Eratosthenes, Euclid’s algorithms, and methods for factorization square roots are a few examples.

It seems common to us now to list things in the order in which we we will do them. But in mathematics, at that time ,— it was not usual.

800s

The story really starts in the 800s with Al-Khwārizmī. His name roughly translates to Algoritmi in Latin, and he developed a technique called Algorism. Algorism is the technique of performing arithmetic with Hindu-Arabic numerals.

Al-Khwārizmī is the first one to develop the concept of the algorithm in mathematics.

1300s

Then came Ramon Llull, who is considered the pioneer of computation theory. He started working on a new system of logic in his work — Ars magna, which influenced the development of a couple of subfields within mathematics, specifically,

  1. The idea of a formal language
  2. The idea of a logical rule
  3. The computation of combinations
  4. The use of binary and ternary relations
  5. The use of symbols for variables
  6. The idea of substation for a variable
  7. The use of a machine for logic

All these led him to pioneer the idea of representing and manipulating knowledge using symbols and logic.

1600s

Then came Blaise Pascal. Pascal was a French mathematician who, at an early age, was a pioneer in the field of calculating machines. Pascal invented the mechanical calculator, and Pascal’s calculator after about 10 years, in 1642. This was an important milestone in mathematics and engineering. It showed the general public that tools can be built, using mathematics, to simplify things, for example, accounting. (Fun fact: He built the first prototype for his father — an accountant!)

Following Llull’s and Pascal’s work, there was Gottfried Leibniz. He made incredible achievements in symbolic logic and made developments in first-order logic. These were important for the development of theoretical computer science. His work still remains:

  • Leibniz’s law (in first-order logic)
  • Leibniz’s Rule (in mathematics)

Leibniz also discovered the modern binary system that we use today . He wrote about it in his paper “Explication de l’Arithmétique Binaire.”

1800s

Charles Babbage, the father of computing, pioneered the concept of a programmable computer. Babbage designed the first mechanical computer. Its architecture was like the that of the modern computer — he called his mechanical computer the Analytical Engine. The Analytical Engine was a general-purpose computer (by today’s standards). It was the first design that we, now, call Turing complete. It incorporated an Arithmetic and Logic unit (ALU), integrated memory, and control flow statements. He designed it, but it wasn’t until 1940s that it was actually built. When he designed it, it was programmed by punch-cards, and the numeral system was decimal.

Working with Charles Baggage on his Analytical Machine was Ada Lovelace. She was the first computer programmer. In her notes on the engine, she wrote the first algorithm that could be run on any machine. The algorithm was to compute Bernoulli numbers. Most of her work contributed to creating the subfield of Scientific Computing. (Fun fact: Her name inspired the programming language Ada!)

Then came a man most computer scientists should know about — George Boole. He was the pioneer of what we call Boolean Logic, which as we know is the basis of the modern digital computer. Boolean Logic is also the basis for digital logic and digital electronics. Most logic within electronics now stands on top of his work. Boole also utilized the binary system in his work on the algebraic system of logic. This work also inspired Claude Shannon to use the binary system in his work. (Fun fact: The boolean data-type is named after him!)

Gottlob Frege defined Frege’s propositional calculus (first-order logic), and predicate calculus. These were vital in the development of theoretical computer science. (Fun fact: The Frege programming language is named after him!)

1900s

In the early 1900s, Bertrand Russell invented type theory to avoid paradoxes in different kinds of formal logic. He proposed this theory when he discovered that Gottlob Frege’s version of naive set theory was in conflict with Russell’s paradox. Russell proposed a solution that avoids Russell’s paradox by first creating a hierarchy of types, then assigning each mathematical entity to a type.

After Russell came the amazing Alonzo Church who introduced Lambda calculus to the world. Lambda calculus introduced a new way of viewing problems in mathematics, and inspired a large number of programming languages. Lambda calculus played a big part in the development of functional programming languages. (Why it is important, and here).

Claude Shannon is famous for his work, the Shannon-Fano algorithm. Shannon founded information theory. He focused on efficiently and reliably transmitting and storing information. At MIT, he wrote a paper that demonstrated the powerful applications of boolean algebra and its electrical applications.

Everyone knows Alan Turing. He formalized a lot of concepts in theoretical Computer Science with his work on the Turing Machine. Turing also contributed heavily to Artificial Intelligence theory — a notable example being the Turing Test. Apart from his research, he was a codebreaker at Bletchley Park during WWII, and was deeply interested in mathematical biology theory. (His work and his papers are deeply insightful — take a look please.)

Grace Hopper was first exposed to Computer Science when she was assigned a role to work on the first large-scale digital computer at Harvard. Her task was to design and implement a method to use computers to calculate the position of ships. In the early 1950s, she designed the language COBOL and built the first program that interprets English code to binary code. Her vision played an incredible part in the development of Computer Science, and she foresaw a lot of trends in computing. (Fun fact: She is credited with popularizing the term debugging!)

Famous physicist John von Neumann was part of the Manhattan Project. But, he’s also important in the history of Computer Science. He designed the Von Neumann architecture. Basically, if you have not heard of it — I am quite certain you have seen the model he came up with:



http://history-computer.com/ModernComputer/thinkers/Neumann.html

One of his biggest principles was the idea that data and program can be saved in the same space. This idea implies that a machine can alter both its program and its internal data.

He contributed to pretty much everything that has any relation to mathematics.

John Backus was the inventor of the FORTRAN language with his team at IBM. Backus many important contributions to functional programming languages and systems. Also, he served on committees developing the ALGOL system of programming languages. Alongside Peter Naur he also developed the Backus-Naur Form. The Backus-Naur Form is used to describe and depict programming languages.

Interestingly, Backus wrote an article titled “Can Programming Be Liberated from the von Neumann Style? A Functional Style and Its Algebra of Programs,” which is worth reading!

Alongside Backus, Peter Naur made major contributions to the definition ALGOL 60 and pioneered the Backus-Naur Form.

Noam Chomsky, a brilliant linguist, has made some indirect and direct contributions to Computer Science. His work on Chomsky Hierarchy and the Chomsky Normal Form are well known in the study of formal grammars.

Edsger Dijkstra is someone we all learn about in our algorithms class. In 1956, he was given the task of showing the power of the ARMAC computer. He came up with the shortest-path algorithm (Dijkstra’s algorithm). Next, ARMAC engineers wanted to cut the copper wire costs. To solve that task, Dijkstra applied a version of the shortest sub-spanning tree algorithm (Prim’s algorithm).

That’s the kind of man Dijkstra was! Dijkstra also formulated the Dining philosophers problem. The xkcd relates to the paper Dijkstra wrote on how Go-to statements are considered harmful.



http://www.xkcd.com/292/

Donald Knuth is a pioneer in the field of analysis of algorithms. He worked on developing both the aspect of finding the computational complexity of algorithms and also the mathematical techniques for performing analysis on algorithms. He’s also widely known for creating the TeX typesetting system, for the book The Art of Computer Programming, for the KMP (Knuth–Morris–Pratt) algorithm, and much much more.



https://xkcd.com/163/

Leslie Lamport laid out the foundations for the field of distributed systems. (Fun fact: he won the Turing Award in 2013. He also lives in New York — so meet him if you get a chance. )

Vint Cerf and Bob Kahn are known as the fathers of the Internet. They designed the TCP/IP protocols, and the architecture of how the Internet would be laid out.

Following their progress, in 1989/1990, Tim Berners-Lee invented the worldwide web. Along with his colleague Robert Cailliau, he sent the first HTTP communication between a server and a client. An important milestone in Computer Science — it represented a new era of communication and also demonstrated the practical nature of theories in Computer Science.

Let me know if I have gotten anything incorrect or have not made anything clear! Also, I wasn’t able to include every individual along the way, but let me know if I’ve missed anyone obvious. Please expand on things I have written through comments.

I also did not go into much detail with every individual. In the future, I am also going to be doing individual posts about each of these individuals. The posts will have more details about their accomplishments.

Resources to learn next:

Key things to research after:

First-order logic, Jacquard loom, Analytical Engine, Boolean algebra, and much more!

One of my favorite talks have been by Donald Knuth. His talk is titled “Let’s Not Dumb Down the History of Computer Science,” is just amazing.



Couple of books:

— Out of their Minds: The Lives and Discoveries of 15 Great Computer Scientists, Dennis Shasha and Cathy Lazere

— Selected Papers on Computer Science, Donald Knuth

Thanks to:

— Snow Pettersen, Freia Lobo

Thanks for reading! If you’d like to checkout some of my other projects — visit my portfolio!

The author of this blog is Abhi Agarwal. Follow him on Twitter - https://twitter.com/abhiagarwal

ThoughtWorks Code-a-thon wants the best programmers from Singapore and ASEAN

ThoughtWorks is one of the coolest IT solutions companies out there today. Apart from being an able software builders, ThoughtWorks is one of the few companies that takes company culture very seriously. They constantly engage with the developer community to know them better and in turn, make ThoughtWorks a great place for them.

They ensure constant engagement with the developer community to know them better and in turn, make its workplace the most sort after.

Concurrent to this philosophy, ThoughtWorks is conducting a programming challenge for developers from Singapore and ASEAN countries.

ThoughtWorks Code-a-thon is 6-hour programming contest, which will feature challenging programming problems. The top 15 programmers from the online event would be invited to ThoughtWorks' Singapore office, where they will engage in a final programming faceoff, to adjudge final winners.



Here's where it gets really good. ThoughtWorks has not held back on the prizes. Some really cool prizes are up for grabs. Winner gets an Xbox One, Oculus Rift, Quadcopters, and many other really great prizes.

Register without any further ado here - https://www.hackerearth.com/thoughtworks-singapore-codeathon-2015/

For more challenges, go to - https://www.hackerearth.com/challenges/
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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

Recommended read: Diversity And Inclusion in 2022 - 5 Essential Rules To Follow

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.

(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?

Hire great developers

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.

Recommended read: How Recruiting The Right Tech Talent Can Solve Tech Debt

#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

  1. 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.
  2. 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.
  3. 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.
  4. 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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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.

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?

2023 Round Up Of Layoffs In Big Tech

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! :)

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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