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.
Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.
Google DeepMindExplain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
Google DeepMindExplain precision versus recall in plain language and how the tradeoff affects product decisions.
Google DeepMindExplain when network interference threatens an A/B test, how it biases estimates, and how to redesign the experiment safely.
Google DeepMindUse PostgreSQL window functions to calculate user running spend and rank users by total spend within each signup cohort.
Google DeepMindDesign a recommendation and ranking system that handles cold start for both new users and new items without hurting feed quality.
Google DeepMindChoose sample size and runtime by combining baseline rate, MDE, alpha, power, and expected traffic.
Google DeepMindFramework for choosing a feature's primary success metric and guardrails before launch.
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Calculate daily campaign conversion rates with conditional aggregation, a CTE, and a campaign dimension join.
Niantic
Braze
OutschoolCompute daily active users and a 7-day rolling average using a CTE, distinct counts, and window functions.
Meta
Spotify
Meta IT