Interviews for data scientist, machine learning engineer, and AI-focused roles comprise several rounds during a typical on-site interview. These interviews assess candidates' prowess in technical (coding, statistics, machine learning, systems design), product (product metrics, product sense, business case), as well as leadership and behavioral skills.
In a typical hour long interview, candidates may get anywhere from 5 to 15 minutes to ask questions to the interviewers. However, most candidates do not prepare or think about questions to ask in advance. This is a big missed opportunity for candidates to learn more about the role, team, org, company, tech stack, culture, leadership values etc. directly from the current employees and future team mates.
In the context of data science, candidates ought to ask pertinent questions that may shed more light on the day-to-day work, projects, teams and the culture in the org. With greater interviewing and real-world data science experience, candidates will be able to better decipher the answers to such questions and read between the lines to make a more informed decision whether to join the company or not.
With everything else being more or less equal amongst the different job offers one may have, the quality of the hiring manager and team, organizational culture, learning and career growth prospects become decisive factors.
Following is a sample list of 20 questions to consider asking the hiring team, in no particular order:
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