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The Johns Hopkins University Data Scientist Interview Questions

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

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1
Machine LearningStart here. 5 questions · ~42 min
Feature Engineering and Model PerformanceEasy

Explain how feature engineering improves supervised model performance and how to validate its impact with proper evaluation.

Feature EngineeringBias-Variance TradeoffSupervised LearningThe Johns Hopkins University
Preprocessing Data With Missing ValuesMedium

Explain how to preprocess missing data for a supervised learning task without introducing leakage or degrading model quality.

Cross-ValidationFeature EngineeringSupervised LearningThe Johns Hopkins University
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2
SQL & Data Manipulation3 questions + 3 drills · ~55 min
3
Behavioral & Leadership8 questions · ~67 min
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4
More topics8 questions · ~67 min
Choose the Right Evaluation MetricsEasy

Pick the right metrics to evaluate a machine learning model and explain why they fit the problem.

PrecisionAccuracyRecallThe Johns Hopkins University
Design a Feature-Concept A/B StudyHard

Design an A/B test to compare two feature concepts, including hypothesis, metrics, power, and a pre-registered decision rule.

ExperimentationGuardrail MetricsA/B TestingThe Johns Hopkins University
Statistical Significance in Hypothesis TestingEasy

Explain what statistical significance means and why it matters when interpreting experimental or analytical results.

Hypothesis TestingData AnalysisStatistical SignificanceThe Johns Hopkins University
Design User Engagement MetricMedium

Tests metric design and operationalization for measuring FIRSTNET GLOBAL user engagement.

product metricsdesignuser engagementThe Johns Hopkins University
Diagnosing Metric DropsHard

Tests root-cause analysis and structured debugging of product metric changes.

performance analysisThe Johns Hopkins University
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