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Updated weekly · Last refresh Aug 30

VTG Data Scientist Interview Questions

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

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1
Machine LearningStart here. 9 questions · ~75 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 TradeoffVTG
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 LearningVTG
Prevent Overfitting in ML ModelsEasy

Explain how to reduce overfitting using regularization, validation, and model selection.

Cross-ValidationBias-Variance TradeoffRegularizationVTG
Predict Customer BehaviorMedium

Train a supervised model to predict customer behavior from historical activity, profile, and interaction data.

Cross-ValidationFeature EngineeringSupervised LearningVTG
Optimizing a Predictive ModelMedium

Tests your approach to model tuning, validation strategy, and diagnosing performance issues.

Hyperparameter TuningCross-ValidationBias-Variance TradeoffVTG
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2
More topics3 questions · ~25 min
A/B Testing for Product FeaturesMedium

Explain how to design and evaluate an A/B test for a product feature, including metrics, MDE, sample size, and guardrails.

Hypothesis TestingStatistical SignificanceA/B TestingVTG
Choosing Classification Evaluation MetricsEasy

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

PrecisionAccuracyRecallVTG
Finding Insights in DataEasy

Tests your ability to derive actionable insights and connect analysis to business decisions.

KPILeading IndicatorsDiagnosisVTG

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