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Wonga Data Scientist Interview Questions

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

25questions
~3htotal time
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1
Machine LearningStart here. 18 questions · ~144 min
Show ML Domain Expertise in Credit RiskEasy

Build and justify a credit default classifier using traditional ML, showing model selection, feature engineering, validation, and explainability.

Hyperparameter TuningNeural NetworksDeep LearningWonga
Predict Loan Default for FintechEasy

Build a supervised classification model to predict 12-month loan default using credit, financial, and application features.

Cross-ValidationFeature EngineeringSupervised LearningWonga
Prevent Overfitting in Loan Default ModelsEasy

Build and compare overfit and regularized classifiers for loan default prediction, and show how cross-validation reduces generalization error.

Cross-ValidationBias-Variance TradeoffRegularizationWonga
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2
Model Evaluation3 questions · ~24 min
Choosing Classification Evaluation MetricsEasy

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

PrecisionAccuracyRecallWonga
Balance Accuracy and InterpretabilityMedium

Tests your ability to trade off model performance and explainability for business stakeholders.

CalibrationAccuracyThreshold TuningWonga
Imbalanced Classes Success MetricsHard

Tests your evaluation metrics and success criteria for imbalanced classification problems.

F1 ScorePrecisionRecallWonga
3
More topics4 questions · ~32 min
Motivation for Data Engineering WorkEasy

Explain what drives your interest in data engineering, grounded in user needs and the value created by reliable data systems.

Jobs to Be DoneUser NeedsValue PropositionWonga
Align Product With User NeedsMedium

A framework for connecting user needs to business goals, then making product decisions with clear trade-offs and measurable outcomes.

User NeedsValue PropositionProduct VisionWonga
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