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Johns Hopkins Applied Physics Laboratory Data Scientist Interview Questions

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

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1
Machine LearningStart here. 4 questions · ~33 min
Supervised vs Unsupervised for Noisy DataMedium

Tests model selection judgment for noisy scientific data and tradeoffs between learning paradigms.

model selectionUnsupervised LearningSupervised LearningJohns Hopkins Applied Physics Laboratory
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2
Behavioral & Leadership14 questions · ~114 min
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3
More topics10 questions · ~81 min
Evaluate Imbalanced Classification ModelMedium

How to evaluate a classification model when the classes are heavily imbalanced.

PrecisionAUC-ROCRecallJohns Hopkins Applied Physics Laboratory
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 IndicatorsDiagnosisJohns Hopkins Applied Physics Laboratory
Pitfalls in Streaming Experiment AnalysisHard

Identify major online experiment pitfalls and explain how they can bias results in a streaming product A/B test.

Network InterferenceNovelty EffectSample Ratio MismatchJohns Hopkins Applied Physics Laboratory
Interpreting Significance in ExperimentsMedium

Explain statistical significance in experiments and how p-values and confidence intervals guide interpretation.

Confidence IntervalsStatistical SignificanceP-ValuesJohns Hopkins Applied Physics Laboratory
SQL Window Functions for Rolling ComparisonsMedium

Tests SQL proficiency with window functions for time-based comparisons and feature engineering.

Window FunctionsLag/LeadRunning TotalsJohns Hopkins Applied Physics Laboratory
Optimizing Large-Scale Data PipelinesMedium

Tests practical pipeline optimization skills for high-volume, high-dimensional data.

data pipelinesperformanceData ModelingJohns Hopkins Applied Physics Laboratory
North Star Metrics for DSMedium

Tests product thinking and ability to define metrics and a North Star KPI for a new data science capability.

North Star MetricKPIJohns Hopkins Applied Physics Laboratory
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
The finish line: interview-readyComplete all 28 questions plus 3 hands-on drills to finish this plan.