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
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.
Those questions actually sound grad level course question.
If you think those are grad level you probably shouldn't be applying for a data scientist position... No offense but they're pretty basic concepts.
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
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.
Ty. Any idea why you didn’t pass? Do you think you messed up the soft questions or were you surprised that you didn’t pass?
Not surprised I didn't pass, I was asked some weird product question about LinkedIn chat or something and I really had trouble bullshitting. I wish I could have said "I think these are terrible ideas we should be thinking about something else". I quickly realized I suck at product questions if it's not about a product/industry I know well (even for that, I didn't pass a phone screen with Quora despite being a power user and thinking I crushed it) , and decided I should try interviewing for engineering positions (elsewhere) instead.