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Deep Dive: How Teamlease And Fresherworld.com Leverage AI & ML To Improve The HR Industry

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Teamlease and Fresherworld.com

According to reports, on average for each corporate job offer in the world, there are 250 resumes. And of those 250, only 4-6 are called for an interview. The insight seems to be ordinary when one just reads it, but, the point is, on average, there are around 250 CVs for one job. That means 250 people fight for that one position. Part of the reason for so many people finding and applying for the open positions is the advent of AI and ML in the HR industry, at least in today’s world.

Some years ago, these online job portals were not in the play, and recruitment and hiring was a tedious offline process, wherein some cases HR managers used to search for candidates offline or through their connections. When the internet became accessible to common people, and many processes became online, the HR industry was quick to follow. There are many players in today’s online job portal market, but one name that is frequently used, especially if one is fresh out of degree college, are Teamlease and its Freshwerworld.com.

Teamlease Services was established in 2002 and is India’s leading HR services company in the organised segment. It’s a Fortune India 500 company with over 2500+ clients and 1900 employees in 8 locations across India.

Teamlease, in its initial days, started recruiting talents offline, that is, its team used to go door to door in search. But, as time passed, when other sectors started moving online and with mobile phones everywhere, they moved online. Now, through their online presence, they have given employment to over 1.7 million people with the aim of making the number bigger. 

As the number of applicants and CVs increased overtime, Teamlease also started to upgrade their tech part; now, they make use of highly advanced technology like AI and ML in their HR processes. 

For our deep dive column, we got in touch with Kaushik Banerjee, Vice President & Business Head, Teamlease and Fresherworld.com to discuss how they leverage AI and ML capabilities.

Use Of AI and ML

With the increasing use of AI and ML in many business sectors and now HR, Teamlease hasn’t shied away from using the AI and ML capabilities. Banarjee says Teamlease completely takes advantage of AI and ML.

The process involves the system carrying the interview process as per the answers given by the candidate. It frames the questions automatically based on CV. The open-ended questions are matched with previously fed data, and there are close-ended questions, which are used for elimination purposes. The algorithm assigns tags based on the CVs and the JD with the percentage of matching criteria to the HR.

The ML matches the words and then provides the contextual reference, resulting in enhancing the accuracy of the result.

Candidates have to structure their CVs better and have to use industry-related keywords inside them. Apart from the names and contact details, the most critical part of a CV, in this case, becomes the objective summary and key skills with spell checks. Including some keywords and phrases related to one’s industry becomes a point of emphasis if one wants to appear in the search net of AI and ML. Apart from the summary and key skills, other spaces where one can include industry-related keywords are projects and key tasks. Including stats and data concerning the respective work is also recommended.

Taking care of all these points helps the managers to choose efficiently and reduce their time, but it will be their risk to depend upon the AI systems.

Teamlease believes that these AI and ML capabilities will definitely not eliminate the need for HR but will only help them ease their tasks in the crowded space, where there are millions of job candidates applying every day.

The Tech Stack And Teamlease’s Hiring

The tech stack with Kaushik’s wing consists of Python, MySQL for the database. PHP7 on the backend and Amazon Web Services for the cloud. The engineering team consists of more than 40 members, and the AI team is around 8.

When it comes to hiring a data science candidate, according to Mr Kaushik Banerjee, the data science sector is relatively new, and there is a need for talent in the market. What they look for in a data scientist is primarily in-depth knowledge about the data. An ideal data science candidate for them must be able to comfortably read data, figure out key insights from it and come up with the best strategy from the provided data.

The Future Roadmap And What Sets Them Apart From Competition

According to Banerjee, what sets Teamlease apart from the competition is their appetite to fulfil the clients’ needs and convert job application to hire as much as possible. They continuously strive to augment their processes with technology and have seen the industry go from 10-12 rounds of interviews to 1 or 2. Now, as for future, with AI and ML capabilities, they envision a future where a candidate will only meet the HR department directly for salary negotiations and not interviews.

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Sameer Balaganur

Sameer is an aspiring Content Writer. Occasionally writes poems, loves food and is head over heels with Basketball.
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