Vishal Gupta


Accelerating Hiring with Data Science

Submitted Apr 15, 2019

At Freshworks, we receive more than 1000 applications every week. This leads to a lot of applications for our Talent Acquisition teams to process, which can be difficult. Conventionally, candidate screening at Freshworks has involved a manual review of the candidate’s resume/portfolio which cannot be scaled for smaller HR teams. We experimented with making this process smoother by implementing an automated pipeline that uses data science to score a candidate based on their skills, experience and how suitable they are for the job they have applied for, using thousands of previously processed candidates.


  • The recruitment pipeline at Freshworks
  • Common roadblocks in hiring and how Data Science can eliminate them
  • Building Candidate Scoring models
    • Data sources and Enrichment
    • Picking the right features for scoring candidates
    • Evaluating the Candidate scoring models
    • Identifying features that differentiate good candidates
  • How candidate scoring models accelerate hiring
    • Candidate conversion rates
    • Average turnaround time
  • AI solutions for the HR in areas other than hiring
    • Targetted training modules
    • Predicting attrition

Speaker bio

As a part of the Data Science team, I work on analysing textual content in deal pipelines and building AI models to boost sales. I enjoy applying AI to solve practical problems.


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