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Prep plan
Updated weekly · Last refresh Aug 30

Costar Data Scientist Interview Questions

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

31questions
~4htotal time
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1
Machine LearningStart here. 7 questions · ~56 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 TradeoffCostar
Handling Missing Data in MLMedium

Explain practical strategies for handling missing data and how to validate that the chosen approach improves model performance.

Feature EngineeringData WranglingSupervised LearningCostar
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2
Statistics & Probability3 questions · ~24 min
Mean on Billions of RowsHard

Tests your ability to compute aggregates efficiently with large-scale data constraints.

Costar
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3
SQL & Data Manipulation5 questions + 3 drills · ~70 min
4
Behavioral & Leadership11 questions · ~88 min
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5
More topics5 questions · ~40 min
Define Success Metrics for FeaturesMedium

Set a clear north star, supporting KPIs, leading indicators, and guardrails for a new product feature.

North Star MetricLagging IndicatorsKPIsCostar
Pitfalls in Streaming Experiment AnalysisHard

Identify major online experiment pitfalls and explain how they can bias results in a streaming product A/B test.

Network InterferenceNovelty EffectSample Ratio MismatchCostar
Predict Customer Churn ApproachMedium

Assesses your end-to-end approach to building and validating a churn prediction model.

User NeedsUse CasesProduct VisionCostar
Diagnose KPI Drop After ReleaseMedium

Diagnose a post-release KPI drop by separating instrumentation issues from real behavior changes and tracing the problem through the metric hierarchy.

KPILeading IndicatorsDiagnosisCostar
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