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.
Explain what statistical significance means and why it matters when interpreting experimental or analytical results.
Design an A/B test for a new checkout installment-flow feature, including metrics, power, guardrails, and a disciplined ship decision.
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Explain how RANK(), DENSE_RANK(), and ROW_NUMBER() differ when ordering tied clinical trial results.
Diagnose a below-expectations product metric drop using decomposition, guardrails, and experiment checks.
Explain the bias-variance tradeoff and how it guides model choice, regularization, and generalization performance.
Evaluates approach to debugging sudden metric declines in a high-scale e-commerce context.
Explain how to profile, clean, and standardize missing or dirty data before analysis.
Optimize a slow PostgreSQL query that aggregates completed transactions while preserving customers with no matching activity.
Capgemini
NomuraDeduplicate customer records with ROW_NUMBER, retaining the latest record and reporting duplicate counts.
IBM
NewWave Telecom & TechnologiesDelete duplicate contact records while retaining the most recently updated row for each email address.
BNSF Railway
Revature