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Google DeepMind Data Scientist Interview Questions

The questions to prepare for a Google DeepMind Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

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1
MetricsStart here. 3 questions · ~26 min
Diagnose a Metric Drop After LaunchMedium

Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.

Lagging IndicatorsLeading IndicatorsDiagnosisGoogle DeepMind
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2
Machine Learning9 questions · ~77 min
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffGoogle DeepMind
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3
Model Evaluation3 questions · ~26 min
Explain Precision Recall TradeoffEasy

Explain precision versus recall in plain language and how the tradeoff affects product decisions.

PrecisionThreshold TuningRecallGoogle DeepMind
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4
A/B Testing & Experimentation4 questions · ~34 min
Network Interference in Collaboration TestMedium

Explain when network interference threatens an A/B test, how it biases estimates, and how to redesign the experiment safely.

Network InterferenceExperimentationA/B TestingGoogle DeepMind
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5
Behavioral & Leadership10 questions · ~85 min
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6
More topics9 questions · ~77 min
Window Functions for Running TotalsMedium
Practice

Use PostgreSQL window functions to calculate user running spend and rank users by total spend within each signup cohort.

Window FunctionsRankingRunning TotalsGoogle DeepMind
Design a Cold Start RankerMedium

Design a recommendation and ranking system that handles cold start for both new users and new items without hurting feed quality.

Cold StartTwo-Tower ModelsRecommendation SystemsGoogle DeepMind
Sample Size for A/B TestsEasy

Choose sample size and runtime by combining baseline rate, MDE, alpha, power, and expected traffic.

Power AnalysisSample SizeA/B TestingGoogle DeepMind
Define Feature Success MetricsMedium

Framework for choosing a feature's primary success metric and guardrails before launch.

MetricsFeature PrioritizationProduct VisionGoogle DeepMind
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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
The finish line: interview-readyComplete all 38 questions plus 2 hands-on drills to finish this plan.