LinkedIn Data Science Team

Chegg snt124
May 23, 2019 22 Comments

Are data scientists at LinkedIn more ML DS roles or analytics, or a mixture of both? Wondering if the roles really require strong skills in python/ML


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TOP 22 Comments
  • LinkedIn MxAu52
    Ds at LI does not develop ML models- there is a track within DS which is more ML focused but for the most part it’s more analytics. If you’re looking for core ML work then interview for the ML/AI track
    May 24, 2019 3
    • Axtria user571
      Yeah and the comment above stated he was asked ML questions as well.

      @tgfi how's DS at Intuit? A recruiter reached out for a senior analyst role, any insights if it's worth pursuing?
      Sep 24, 2019
    • Apple Justdance
      Can DS work on some machine learning projects?
      Oct 18, 2019
  • Amazon / Data pozbuw
    I interviewed for a ds position at sunnyvale, and yes it was analytics, ie not writing production codes for ml or ai products, but more focused on supporting decision making with data. The interview was not easy btw, there were product case study questions, advanced stats topics like whats your favorite kernal function, describe a difference between l1 and l2 regularization and talk about when you used either and why, but no r or python coding, but leetcode medium sql questions.
    May 23, 2019 10
    • Goldman Sachs fake engineer
      I babysit mounds of technical debt...:( It would be fine if the comp were above average, but it's the opposite, so trying to gtfo

      Anyways back on topic, it's true a lot of product analytics roles won't ask this stuff. In those cases, you should be good at the product case question BS. I think it's mainly about following the consulting interview format where you give your "structured" response, since that's what makes people feel good.

      There really isn't an excuse for not memorizing the answers to a bunch of the really standard stats questions though. All the stuff you can find in a textbook about linear regression (Gauss Markov, regularization, standard errors, t stats), all those probability/combo brainteasers, those "what is the variance of blah conditioned on blah" questions, etc.
      May 23, 2019
    • Axtria user571
      Amazon, I am interviewing for this position, mind if I dm you?
      Sep 24, 2019
  • Goldman Sachs fake engineer
    When I applied there were two different job titles, machine learning engineer and data scientist. I'm pretty sure data science is much more analytics focused. I was only asked soft questions during the phone interview for data scientist and didn't pass.
    May 23, 2019 6
    • LinkedIn flurple
      “I think these are terrible ideas we should be thinking about something else" could be a pretty good answer to an interview q, if you have some better ideas for what to do instead.
      May 24, 2019
    • Axtria user571
      How was the coding level?
      Sep 24, 2019


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