Top 37
Prep plan
Updated weekly · Last refresh Aug 30

Factual Data Scientist Interview Questions

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

37questions
~5htotal time
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1
SQL & Data ManipulationStart here. 8 questions + 2 drills · ~87 min
2
Machine Learning4 questions · ~34 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 TradeoffFactual
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3
Statistics & Probability3 questions · ~25 min
Sample Size and Power PlanningMedium

Reason about sample size, power, and minimum detectable effect before launching an experiment.

Hypothesis TestingPower AnalysisSample SizeFactual
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4
Metrics5 questions · ~42 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 IndicatorsDiagnosisFactual
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5
Behavioral & Leadership10 questions · ~84 min
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6
More topics7 questions · ~59 min
Design Test for New FeatureMedium

Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.

experiment designfeature evaluationA/B TestingFactual
Choosing Classification Evaluation MetricsEasy

Explain which classification metrics to use and how metric choice depends on the business objective and error tradeoffs.

PrecisionAccuracyRecallFactual
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityFactual
Choose a Feature Success MetricHard

Framework for choosing the right primary success metric for a new feature, including leading indicators, guardrails, and business alignment.

Feature PrioritizationValue PropositionProduct VisionFactual
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The finish line: interview-readyComplete all 37 questions plus 2 hands-on drills to finish this plan.