I'm an L6 Data Science Manager - Product at Google and I have received feedback that my IC skills are weak. Looking to do a lateral move, e.g. Meta, and as the title says I want to get help studying, building IC portfolio, and career advice. I have 15+ years in data science, 5+ as a manager, and a PhD in a relevant field. I joined Google a couple years ago and failed the Data Science - Research interview due to lack of Python skills. We were using SAS/SPSS back when I was an IC, and although I have taken a ton of classes and managed projects in Python I don't have the IC skills there. My background is in ML, but mostly basic stuff like k-means and logistic regression. Also looking to upskill my ML, and refresh my memory on everything in data science technical interviews, e.g. basic statistics. My IC work since joining Google consists of building data pipelines and dashboards. I'm looking at an online class like this to help me interview prep, and I think it would also be helpful to build an IC portfolio, and get some career advice: https://professional-education-gl.mit.edu/mit-online-data-science-program Any recommendations? Google L6 Data Science - Product TC 600k
I'm in a similar boat, but what do you mean by building IC portfolio? AFAIk that's not a thing unless you are applying for an entry role, unless you mean like research publications.
I was never asked for an IC portfolio before applying internally at Google, but it's what we call artifacts. Nothing done for fun or education counts, though. I think a lot of people have GitHub sites full of their work or at least one passion project that they can share when applying for jobs. Maybe I'm in an awkward spot here not having crossed into exec territory yet, but many years since I was IC. In interviews I get asked to share technical details of a project I worked on and sometimes I don't know enough about what my reports did to answer and other times I think I get points taken off, because I didn't personally write the code.
This is so interesting, in a similar boat especially from an interviewing standpoint. Would be great to share notes ... will dm
Seems like meta does not match Google TC for DS in case of parallel move. Will have to be level up to match TC I guess. Are you a TLM or a manager? If TLM then you probably write some code so why are points taken off? If manager then why are your IC skills come into question? Overall it's not clear why you need to do the courses, apart from personal development, which is surely a good use of time. You can just cram for leetcode to pass interview (python or SQL) and ask your reports for details of the projects you plan to speak about. Use khan academy for basic stats refresh and udacity course on a/b testing for experimentation. This is all that is needed anywhere but at Google to pass ds interviews.
Thanks for the tips. I'm a manager, not sure TLM is even a thing in Data Science. L6 DS interview includes more leadership stuff, but is otherwise technically the same as L5. I know, because I'm an interviewer for both. It's embarrassing how many L,6 candidates fail the SQL and stats part of the interview.
Levels.fyi DS is roughly 450k for meta IC6 and Google L6. I don't trust the DS manager data as I'm sure it's low sample size.
What you did as IC sounds more like mlops, not ds or ml. What did you do as a manager? If you were not ppl manager, and tech savvy helping reports working on ml or ds, then I think you can use it, could be viewed as ml/ds person.