FARFETCH Data Scientist Interview Questions
The questions to prepare for a FARFETCH Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Explain how to establish statistical significance in A/B tests using hypotheses, power, confidence intervals, and safeguards against false positives.
Design an A/B test for a new checkout installment-flow feature, including metrics, power, guardrails, and a disciplined ship decision.
Diagnose a below-expectations product metric drop using decomposition, guardrails, and experiment checks.
Explain how RANK(), DENSE_RANK(), and ROW_NUMBER() differ when ordering tied clinical trial results.
Explain the bias-variance tradeoff and how it guides model choice, regularization, and generalization performance.
Explain what statistical significance means and why it matters when interpreting experimental or analytical results.
Explain how to profile, clean, and standardize missing or dirty data before analysis.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
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Optimize a slow PostgreSQL query that aggregates completed transactions while preserving customers with no matching activity.
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