Data Scientist interviews at top companies (Meta, Amazon, Netflix, Stripe) test four skills: SQL, statistics, machine learning fundamentals, and product/case-study thinking. The loop varies in proportion — Netflix is heavier on causal inference, Amazon is heavier on case studies, Meta is heavier on SQL — but the skills are the same. Here is what each round actually scores.
SQL — Where Most Candidates Lose Points
Window Functions, Not Just Joins
Every loop has at least one problem requiring window functions — typically ROW_NUMBER, LAG/LEAD, or a running sum. Candidates who only practise GROUP BY and JOIN fail these. Practise 'find the second-most-recent order per customer' until it is automatic.
Date Math and Cohort Analysis
Expect a problem that involves grouping users by signup-month cohort and tracking retention by month-since-signup. The trap is forgetting to use signup-date as the cohort key, not order-date.
Machine Learning Conceptuals
Bias-Variance, Regularisation, and Cross-Validation
Be ready to explain L1 vs L2 in 90 seconds with a real use case (L1 for feature selection, L2 for multicollinearity). Be ready to explain why k-fold cross-validation is preferred over a single train/test split (variance reduction, especially on small datasets).
Precision vs Recall — Pick the Right Metric
Interviewers will ask 'how would you measure this model?' — the right answer depends on the business cost of false positives vs false negatives. Spam filter? Optimise precision. Cancer screening? Optimise recall. Always tie metric to business cost.
Case Studies
Structure Your Case Answer
"User engagement dropped 15% last week. Why?" Walk through: clarify the metric, segment by platform/geo/cohort, isolate seasonality, generate hypotheses, propose how to test each. The mistake is jumping to a hypothesis without segmenting the data first.
A/B Test Pitfalls
Expect questions about novelty effects, peeking, multiple-comparison correction, and Simpson's paradox. The best preparation is to know the three or four classic pitfalls cold so you can spot them on the fly.
InterviewLift's DS prep includes a 200-question SQL drill set graded against the exact rubrics from Meta and Stripe, plus a case-study judge that scores your answer on the seven dimensions interviewers use internally.
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