Data Science Hiring Process At Bigbasket

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Data scientists at Bigbasket have to juggle multiple responsibilities since they are part of a small team supporting a growing and dynamic startup business.

The analytics and data science at Bigbasket is centrally located. Set up in 2013, the 10-member team works with various partners to focus on key business deliverables: analytics work products (reports, dashboards, deep-dives, etc. used by business teams directly) and data science work products (ML models, and OR models that power product features that benefit customers). The team also manages the end-to-end analytics ecosystem, including analytics infrastructure, analytics data pipelines, and deployment of analytical solutions and data science models. 

To understand more about the data science team and the hiring process, we got in touch with Subramanian MS, head of category marketing and analytics at Bigbasket. 

Required Skills

Subramanian said deep expertise and problem-solving skills are a must in an analytics professional. The expertise includes a solid understanding of algorithms, operation research and machine learning skills. “Some of the overarching traits we look for in all recruits include attention to detail, ownership and proactiveness etc. We believe these are key traits to succeed in the fast-paced, startup environment of Bigbasket,” he added. 

In terms of educational background, Bigbasket looks for engineering graduates with or without experience. As Subramanian shares, many of their team members have pursued and completed advanced machine learning and artificial intelligence programs before joining Bigbasket or, in some cases, while at Bigbasket.

Subramanian said some of the vital skills are problem-solving, analytical thinking, communication skills, attention to detail, ownership and proactiveness. Educational background is further used as a filter to shortlist candidates.

Interview Process 

Subramanian detailed the interview process for candidates, both experienced and fresher. 

The interview process for experienced candidates:

  • SQL test since it is a critical skill used every day by analytics and data science professionals
  • Setting up interviews with other team members to understand the cultural and experiential fit

The interview process for fresh hires:

  • An assessment focused on understanding a candidate’s analytical, reasoning and verbal skills 
  • Setting up interviews to help the candidate understand more about the opportunity and the interviewers to assess if the candidate will be a good fit

The traditional methods Bigbasket relies on recruiting are campus hiring, sourcing candidates through hiring partners and referral from Bigbasket employees. The non-traditional methods include a partnership with entities that offer online programs in analytics and data science, and social media, including LinkedIn.

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