Top 41
Prep plan
Updated weekly · Last refresh Aug 30

LinkedIn Data Scientist Interview Questions

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

41questions
~6htotal time
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1
MetricsStart here. 4 questions · ~34 min
2
Machine Learning6 questions · ~50 min
Bagging vs Boosting ExplainedMedium

Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.

Ensemble Methodsmodel trainingSupervised LearningLinkedIn
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3
Statistics & Probability4 questions · ~34 min
Understanding Type I and Type II Errors in TestingMedium

Differentiate between Type I and Type II errors in hypothesis testing with a practical example.

Hypothesis TestingStatistical SignificanceP-ValuesLinkedIn
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4
A/B Testing & Experimentation4 questions · ~34 min
Diagnose Sample Ratio MismatchHard

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

Guardrail MetricsSample Ratio MismatchA/B TestingLinkedIn
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5
SQL & Data Manipulation3 questions + 3 drills · ~55 min
6
System Design3 questions · ~25 min
End-to-End ML System for PYMKHard

Tests system design for a LinkedIn recommendation pipeline with production monitoring.

ML RankingRetrievalRecommendation SystemsLinkedIn
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7
More topics17 questions · ~143 min
Evaluate Imbalanced Model PerformanceMedium

Evaluate a model on an imbalanced dataset and judge whether accuracy is misleading.

F1 ScorePrecisionRecallLinkedIn
Batch vs Stream Processing Trade-offsMedium

Compare batch and stream processing across latency, complexity, cost, and data quality in a modern analytics pipeline.

InfrastructureStream ProcessingETLLinkedIn
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The finish line: interview-readyComplete all 41 questions plus 3 hands-on drills to finish this plan.