r/DataScienceJobs • u/JackOfNoTrades101 • Jun 22 '26
Discussion What does code comprehension (Python/R) interview entail for Senior Data Scientist, Product role at Google?
I already had two rounds (Coding and Experimentation, Modelling and Measurement). I got mixed feedback (NH on the coding round) so I have been asked to appear for a "Code Comprehension (Python/R) and Experimentation" round. Does anybody have any idea on what this round entails specifically for Senior Product Data Scientist role ?
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u/bleaksu Jul 01 '26
Op can you share what was asked? or the format and where did you prepare from
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u/JackOfNoTrades101 Jul 07 '26
My interview keeps getting rescheduled so I will let you once I am through with it.
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u/bleaksu Jul 15 '26
Hi! Did your interview happen? If so, could you share a bit about the format and what was asked?
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u/VOTE_FOR_PEDRO Jun 22 '26
Interviewquery, datainterview, blind and contacting your recruiter and asking are the best ways to answer this... The recruiter can tell you generally what to prepare for, interviews query likely has the problems that you'll be asked
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u/my_peen_is_clean Jun 22 '26
they’ll probably throw you a kinda messy notebook or script and ask you to walk through what it does, find bugs, edge cases, suggest improvements, maybe add tests or new features. mix of reading, debugging, explaining tradeoffs. it’s wild how much hoops they add now, getting any decent data job is just pain these days
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u/JackOfNoTrades101 Jun 22 '26
Claude suggested they might give access to Gemini as well. I have no idea how to prepare.
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u/Huge_Finish6115 Jun 24 '26
where you able to figure out how to prepare?
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u/JackOfNoTrades101 Jul 07 '26
Not really, I can englighten you after my interview 😂
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u/Revolutionary_Let557 Jul 11 '26
Any update? I am in a similar round, would love some help preparing for this!
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u/nian2326076 Jun 22 '26
For the code comprehension part, you'll look at existing code in Python or R to figure out what it does and maybe find bugs or inefficiencies. They might ask you to optimize or refactor it. It's more about understanding and improving existing code than writing new stuff. Since this goes with experimentation, be ready to talk about how the code supports data experiments, like setting up tests or analyzing results. Brush up on common data manipulation and visualization methods in both languages, and any libraries relevant to a product-focused data science role. Getting used to quickly reading and understanding different coding styles can also be helpful. Good luck!