Data Scientist Statistics & Math Interview Questions
Statistics for a Data Scientist is graded out loud: no console, no code, just whether you can name the right distribution and defend the choice. Across these 503 questions, candidates at Meta, Capital One, Google, Uber and Citadel are asked to describe the shape of a comment-count distribution and justify why it is right-skewed rather than normal, work out the probability of a fourth good response after three successes, reason about who is missing from a survey sample, and defend what a p-value does and does not tell them. Regularisation, resampling and the metrics worth reporting for an imbalanced classifier come up about as often as pure probability. Capital One is unusually heavy here at 57, which shows in the credit-risk framing of several questions, and Citadel's 16 pull toward expected value and combinatorics. The difficulty spread is wider than on any other Data Science topic in the bank: 116 easy warm-ups checking whether you still remember what variance is, against 88 hard ones where the answer needs an actual derivation. 414 carry a written solution and 81% are readable without a premium account.
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