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Updated weekly · Last refresh Aug 30

Factset Data Scientist Interview Questions

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

25questions
~3htotal time
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1
Machine LearningStart here. 5 questions · ~41 min
Stock Price Forecasting ApproachHard

Build a stock price forecasting pipeline using time series validation, careful feature engineering, and realistic error metrics.

Feature EngineeringSupervised LearningFactset
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffFactset
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2
Statistics & Probability4 questions · ~33 min
Mean and Standard Deviation BasicsEasy

Compute the mean and standard deviation of a dataset, and distinguish the sample standard deviation from the population version.

DistributionsVarianceExpected ValueFactset
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3
SQL & Data Manipulation3 questions + 3 drills · ~54 min
4
Behavioral & Leadership9 questions · ~73 min
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5
More topics4 questions · ~33 min
Define Metrics for New FeaturesMedium

Define a success metric for a new feature that captures real user value, not just raw usage.

MetricsFeature Prioritizationuser valueFactset
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 IndicatorsDiagnosisFactset
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 TestingFactset
Prioritize Features for AI ProductsMedium

A framework for prioritizing AI product features based on user value, feasibility, evaluation quality, and trade-offs.

Feature PrioritizationValue PropositionFactset

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