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Updated weekly · Last refresh Aug 30

Dana-Farber Cancer Institute Data Scientist Interview Questions

The questions to prepare for a Dana-Farber Cancer Institute Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

33questions
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1
SQL & Data ManipulationStart here. 7 questions · ~66 min
SQL Cohort and Timeline QueryMedium
Practice

Identify Dana-Farber patients with Condition B after Treatment A using joins, a CTE, and PostgreSQL date arithmetic.

Date FunctionsJoinsData WranglingDana-Farber Cancer Institute
Dense Rank Performance by DepartmentMedium
Practice

Rank completed experimental runs within each department using PostgreSQL DENSE_RANK and score-based tie handling.

RankingsqlDana-Farber Cancer Institute
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2
Machine Learning6 questions · ~57 min
Predict 30-Day Readmission ModelMedium

Tests end-to-end modeling skills for a clinically meaningful prediction task.

Cross-ValidationFeature EngineeringSupervised LearningDana-Farber Cancer Institute
Rare Positive Class HandlingHard

Tests your approach to imbalanced classification and evaluation for rare clinical events.

Cross-ValidationFeature EngineeringSupervised LearningDana-Farber Cancer Institute
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3
Statistics & Probability9 questions · ~85 min
Multiple Comparisons CorrectionHard

Tests your ability to control false positives in high-dimensional genomic analyses.

Hypothesis TestingStatistical SignificanceP-ValuesDana-Farber Cancer Institute
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4
A/B Testing & Experimentation4 questions · ~38 min
Pitfalls in Concurrent Overlapping TestsMedium

Assesses your understanding of experimental validity under overlapping treatments and interference.

A/B TestingDana-Farber Cancer Institute
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5
Behavioral & Leadership4 questions · ~38 min
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6
More topics3 questions · ~28 min
Core Metric for Clinical Data PipelineMedium

Assesses how you translate pipeline changes into measurable outcomes for clinical collaborators.

Dana-Farber Cancer Institute
Diagnose Engagement Drop Root CauseMedium

Tests your metrics debugging skills and structured root-cause analysis.

Data AnalysisDiagnosisuser engagementDana-Farber Cancer Institute
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