Online coding: Imo the most difficult part of the process due to some awkward wording. Also a very quick fire exercise, essentially run out of time. 3 parts: SQL, Python, generic ML knowledge. Past tech experience: just make sure that you know what you did and why (may require brushing up on DS knowledge). Tech case interview: 'This is a problem, how would you build a DS model around it', from there a rather normal case. Personal Experience: same as for generalist consultant Final case + personal experience: same as for generalist.
Sr Data Scientist Interview Questions
3,392 sr data scientist interview questions shared by candidates
Fill gaps for the XBoost Tree, write SQL queries, why would I prefer a single model to group one; talk a lot about challenges and how I solved them during the PEI part.
Explain a solution at your current role
Tell me about yourself, case study, comp industry benchmark questions, etc.
How would you build a ML model to test for scams on the WWE app?
What is the expected value of various descriptive statistics of certain outcomes among a randomly generated pair of numbers. Completely ungrounded in any sort of business or real-world scenario, basically just a math quiz.
project based questions, RAG arch, LLM fine tuning, ...
How to treat categorial features in classification problems.
What is your availability like for the next two weeks
Round 1: some basic python coding Round 2: sent a dataset over email, then asked to convert that into pandas dataset, then some very basic operation on it
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