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Prep plan
Updated weekly · Last refresh Aug 30

Stanford University Data Scientist Interview Questions

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

43questions
~6htotal time
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1
SQL & Data ManipulationStart here. 7 questions · ~62 min
SQL for Monthly Facility UsageMedium
Practice

Rank Stanford University facilities monthly by utilization within each student cohort using CTEs and window functions.

Window FunctionsDate FunctionsRankingStanford University
Rank Applicants With Window FunctionsEasy
Practice

Rank Stanford University grant applications within each department using average review scores and the RANK window function.

Window FunctionsRankingStanford University
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2
Statistics & Probability9 questions · ~80 min
P-Values and Confidence IntervalsEasy

Tests your ability to explain statistical concepts clearly to non-technical decision makers.

Confidence IntervalsStatistical SignificanceP-ValuesStanford University
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3
Machine Learning6 questions · ~53 min
L1 vs L2 RegularizationEasy

Tests your understanding of regularization math and practical model selection tradeoffs.

Hyperparameter TuningFeature EngineeringRegularizationStanford University
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4
A/B Testing & Experimentation6 questions · ~53 min
Common A/B Testing PitfallsMedium

Assesses knowledge of experiment failure modes that distort conclusions.

Data AnalysisStanford University
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5
Product Sense6 questions · ~53 min
Engagement and Utility MetricsMedium

Tests your ability to define metrics that capture both usage and value for research users.

Engagement MetricsStanford University
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6
Behavioral & Leadership6 questions · ~53 min
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7
More topics3 questions · ~27 min
NLP Pipeline for Medical DiagnosesHard

Tests your NLP pipeline design skills for information extraction from unstructured clinical text.

Text ClassificationNamed Entity RecognitionTokenizationStanford University
Composite Index for Data QualityMedium

Tests your metrics design and aggregation approach for multi-source data quality measurement.

Data QualityStanford University
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