Case Study

How ZS increased their ML talent pool by reducing their recruitment cycle

About ZS Associates

ZS is the world’s largest firm that is focused exclusively on helping companies improve overall performance, revenue and market share. It is involved in end-to-end sales and marketing solutions—from customer insights and strategy to analytics, operations, and technology. More than 4,500 ZS professionals in 22 offices worldwide draw on deep industry and domain expertise to deliver meaningful impact for clients across multiple industries.

ZS focuses exclusively on the two areas that create customer demand: sales and marketing. As a result, its expertise in this domain is both broad and deep. It provides a vast range of marketing- and sales-related services in the industry, from customer insight, product development, and sales and marketing strategies, to sales-compensation planning and even administration planning, to name a few.

Since 1983, ZS has been working shoulder-to-shoulder with leaders at some of the world’s top corporations by helping them:

  • Gather and analyze data to create the best strategies
  • Orchestrate sales and marketing activities to increase demand efficiently
  • Change quickly to become more competitive

What was the initial hiring process like before partnering with HackerEarth?

ZS depended on the traditional hiring model for recruiting Machine Learning talent. The typical hiring process consisted of:

  • An initial screening round where the recruitment team would connect with candidates to better understand whether they are suitable for the role
  • Telephonic interview with the hiring manager
  • Post the telephonic interview with the hiring manager, further rounds of interviews including a case study round were scheduled to assess the candidate better

Since the decision to take the candidature further was purely based on interaction with little emphasis on technical evaluation at the beginning of the process, a lot of candidates who qualified for further rounds did not have the expertise needed or had no hands-on experience in Machine Learning.

The candidates who did make it to the evaluation through the case study round had their own set of problems as several of the problem statements couldn’t be solved within the stipulated time. This process did not prove to be candidate-friendly and the hiring team found it difficult to close positions within the given time.

Role of HackerEarth's Technical Recruitment software in streamlining the hiring process

ZS used HackerEarth’s Technical Recruitment software as their platform of choice to recruit Data Scientists for their Machine Learning requirements. Since it needed in-depth tests to evaluate prospective talent for the role, Machine Learning questions were customized by the team at HackerEarth and provided on the platform. The ZS Talent Acquisition team used these questions based on the position they were evaluating talent for. The platform helped scale internal hiring as well as hiring from universities as a part of their Young Data Scientist program. The platform also helped scale the recruitment efforts of the ZS team and contributed significantly to securing the right Machine Learning talent for the organization.

Impact of using HackerEarth's Technical Recruitment software vs. the traditional hiring process

Internal recruitment

Before using HackerEarth’s Technical Recruitment software as a hiring platform, the quality of potential hires that the company received was low. Also, candidates who did not qualify for the role or were genuinely not interested in the role were also a part of the pipeline and under active consideration. To manually sort the right candidates from the existing pipeline was a tedious job for the Talent Acquisition team.

Once HackerEarth’s platform was chosen as the platform for technical recruitment, the quality of candidates drastically increased to an extent that the potential talent pool consisted of genuine Machine Learning enthusiasts which directly impacted the quality of submissions during the evaluation process.
The TA team was able to eliminate the telephonic round from their evaluation process thus bringing down the number of rounds from 6 to 4. The recruitment cycle also reduced and the number of offers rolled out to Data Scientists went up from a single offer across a span of 6 months to close to 4 offers!

Hiring from universities

In their Young Data Scientist program, ZS actively recruits Data Scientists for Associate roles right off campus. It has been able to successfully tap into young talent by actively using HackerEarth’s platform during campus drives across 80 universities. ZS also rolled out 11 offers for Associate Data Scientists in 2016 and the number has gone up since then with 16 offers rolled out in 2017.

How was the experience with HackerEarth?

The overall experience with HackerEarth has been amazing. The team is very helpful and proactive. They assisted us in marketing our signature event–Young Data Scientist Challenge –and ensured its smooth implementation in a timely manner.

Silky Sethi,
Senior Human Resource Associate- Recruitment


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