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American Express Data Scientist Interview Questions

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

Random Forest vs Gradient Boosting
Medium

Compare Random Forest and Gradient Boosting, then choose the right ensemble for a supervised learning task.

Ensemble MethodsBias-Variance TradeoffSupervised Learning
American Express
Detect Rare Payment Fraud
Medium

Build an imbalanced binary classifier for payment fraud detection using cost-sensitive learning, threshold tuning, and precision-recall evaluation.

Cross-ValidationFeature EngineeringSupervised Learning
American Express
Handle Missing and Skewed Features
Medium

Prepare messy tabular data with missing values and skewed features before training a predictive model.

Cross-ValidationFeature EngineeringSupervised Learning
American Express
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First Checks for Metric DropsEasy

Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.

Lagging IndicatorsLeading IndicatorsDiagnosis
American Express
Diagnose Activation Conversion Drop
Hard

Investigate why signup to activation conversion fell from 41% to 29% after onboarding and acquisition changes.

Funnel AnalysisConversion RateDiagnosis
American Express
Define Metrics for New FeaturesMedium

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

MetricsFeature Prioritizationuser value
American Express
Optimize High Risk Product Onboarding
Medium

Approach for improving onboarding to a high-risk financial product while balancing conversion, compliance, and user protection.

onboardingUser NeedsConversion Rate
American Express

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Diagnose Sample Ratio Mismatch
Hard

Investigate sample ratio mismatch and decide whether an experiment readout is trustworthy enough to ship.

Guardrail MetricsSample Ratio MismatchA/B Testing
American Express