Halfway into 2023, and over two lakh employees world over have already been laid off. Amidst this crisis crippling the job market, AI-powered HRTech platform Instahyre is making sure to provide the best of opportunities.

In solving the pain of millions of job seekers, Instahyre’s data science team has successfully tackled one of their primary challenges by optimising the job-matching process through ‘Instamatch’ their proprietary recommendation system. It improves the efficiency and effectiveness of the job search experience for both job seekers and employers.

“Instamatch has changed how companies approach hiring, changing the modus operandi from mass emails, keyword search, and unanswered phone calls to a holistic data-driven, tech-based candidate personality and company DNA mapping, which has taken candidate experience and hiring conversions to a whole new level, reducing the time and cost to hire drastically,” said Sarbojit Mallick, cofounder of Instahyre, in an exclusive conversation with Analytics India Magazine.   

Founded in the year 2017 by Aditya Rajgarhia and Mallick, Instahyre’s adept use of AI, ML and data science in its operations has resulted in an optimised recruitment platform that provides personalised job matches, streamlined candidate evaluation, and improved efficiency for recruiters and candidates alike.     

The company boasts about a 70% reduction in time to hire and cutting costs by thrice compared to traditional methods. With over 10,000 companies benefiting from their services and a staggering 40 million candidates on their platform, Instahyre has earned the trust of major industry players such as Amazon, Google, PayPal, Salesforce, Walmart, Oracle, Razorpay, Paytm, PhonePe, JP Morgan, Adobe, and Myntra.    

Inside the AI and ML Operations of Instahyre

In its operations, Instahyre effectively implements AI and ML to harness the power of data science and derive valuable insights. 

A prominent area where data science is applied at Instahyre is in candidate-company matching. Using InstaMatch, the data science team ensures that job seekers are matched with companies based on a comprehensive set of factors, including skills, experience, and individual preferences. This results in a more precise and personalised job-matching experience for users.

Additionally, Instahyre employs natural language processing (NLP) and machine learning algorithms to parse and analyse resumes and allows the platform to extract relevant information from resumes, allowing for a streamlined and time-saving candidate evaluation process for both job seekers and employers. The platform has been utilising generative AI since its inception six years ago. 

Moreover, Instahyre assists recruiters with tools like Instahyre Talent Insights, which provides a global overview of the talent pool for each job post. The AI-driven approach automates various aspects of the hiring process, including candidate sourcing, shortlisting, and scheduling interviews. It also conducts deliberate screening and assessment, leading to effective candidate evaluation and offer rollouts for chosen individuals.

Tech Stack Employed

Instahyre uses various technology capabilities, including an Application Tracking System (ATS) Integration. It is integrated with widely-used applicant tracking systems used by employers and recruiters. This facilitates a smooth transfer of candidate data, updates application statuses, and streamlines the entire hiring process for the company.

Furthermore, the data science team at the company employs a range of tools, applications, and frameworks to tackle challenges and make informed decisions. These resources encompass MySQL, Python, Java, NLP, and other relevant technologies. By combining these tools, they aim to excel in data-driven endeavours and maintain a dynamic work environment.

Interview Process

Instahyre seeks potential candidates with specific expertise in different domains. For the ML Engineer role, they require proficiency in Python, NLP, and other deep learning concepts. For the Data Engineer position, the desired skills encompass Python, Java, and Scala, as well as experience with technologies like Hadoop, Spark, Kafka, MySQL, MongoDB, Cassandra, AWS, and Azure.

Their data science hiring process involves multiple steps to find the right candidates that begins with a thorough review of resumes, focusing on educational background, work experience, and essential skills in mathematics, statistics, programming, and machine learning. Shortlisted candidates then undergo a technical assessment, evaluating their abilities in data analysis, programming languages, statistical modeling, and problem-solving.

Successful candidates proceed to a technical interview, where their expertise and problem-solving capabilities are extensively examined. Lastly, behavioural interviews assess candidates’ communication skills, problem-solving approach, and cultural fit within the collaborative team environment.

Expectations

Once selected, candidates joining the data science team at Instahyre can expect a dynamic and intellectually stimulating environment. They will have the opportunity to work on cutting-edge technologies, solve challenging problems, and collaborate with a highly skilled and diverse team. The company provides access to the latest tools and resources to support their work and encourages continuous learning and professional development.

“In return, Instahyre expects candidates to have a solid foundation in data science, including a strong understanding of statistics, mathematics, and machine learning algorithms, added Mallick.

Excellent programming skills, strong analytical thinking, problem-solving abilities, and effective communication of complex ideas are also highly valued qualities expected from candidates joining the data science team.

Mistakes to Avoid

When interviewing for a data science job at Instahyre, candidates should avoid some common mistakes that can hamper their chances. One mistake is not showing practical experience and how their work has made a real-world impact. Candidates should share specific project examples, challenges they faced, and the outcomes they achieved.

Another mistake is not preparing well for technical questions or lacking a good understanding of core data science principles. Being well-prepared and showing mastery of important concepts is important to impress the interviewers. Candidates should highlight their practical experience with different datasets and explain how their work has made a difference. Instahyre values innovation, creativity, and a growth mindset, so applicants should try to embody these qualities

Work Culture

“Our work culture is positive and the best part is there is no micromanagement. Employees are trusted and given autonomy to handle their tasks, leading to increased productivity and accountability,” added Mollick. The company follows a remote work policy, allowing employees to work from their preferred locations, allowing Instahyre to tap into talent from diverse geographic areas.

“What sets Instahyre apart from its competitors, especially in terms of working with the data science team, is its collaborative and cross-functional approach, he added.

The company encourages collaboration between data science and other teams, fostering diverse perspectives and knowledge-sharing to solve complex problems. It also places a strong emphasis on innovation and continuous learning, offering opportunities for professional development and research activities. 

So if you want to work on impactful projects that directly benefit users and the recruitment industry as a whole but also grow professionally and personally, Instahyre is the place for you. Check out their careers page now.

Read more: Data Science Hiring Process at Naukri.com