Deepmind Data Scientist Interview Questions
The questions to prepare for a Deepmind Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
DeepmindExplain how to choose, transform, and validate features for a predictive model using a structured ML workflow.
DeepmindFramework for choosing a feature's primary success metric and guardrails before launch.
DeepmindInvestigate why a key KPI moved the wrong way after a product change and separate signal from noise.
DeepmindExplain what cross-validation is and why it matters when choosing between models.
DeepmindDesign an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.
DeepmindTests understanding of regression assumptions needed for reliable inference and prediction.
DeepmindTests ability to write SQL for partitioned ranking across time windows.
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Use joins, CASE WHEN, and date filtering to compare outcome rates before and after a decision.
HarbourVest PartnersBuild a daily series and compute a 30-day trailing moving average of task bookings using window functions.
TaskRabbit
RBCUse a CTE, joins, and RANK() to find the top 2 clients by revenue for each product from completed 2024 orders.
Google
Publicis Groupe
RTX