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Prep plan
Updated weekly · Last refresh Aug 30

Barclays Data Scientist Interview Questions

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

50questions
~7htotal time
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1
SQL & Data ManipulationStart here. 7 questions + 2 drills · ~78 min
2
Pipelines6 questions · ~50 min
Data Quality in ML PipelinesMedium

Practical approach for maintaining data quality across ML ETL pipelines, orchestration, and repeatable data processing.

Data QualityETLData ModelingBarclays
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3
Model Evaluation6 questions · ~50 min
Diagnose Production Model UnderperformanceHard

Approach for diagnosing and fixing a model that underperformed after deployment.

Confusion MatrixCalibrationThreshold TuningBarclays
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4
Machine Learning7 questions · ~58 min
Customer Segmentation with ClusteringMedium

Segment customers into actionable groups using clustering and engineered behavioral features.

ClusteringFeature EngineeringSupervised LearningBarclays
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5
Statistics & Probability6 questions · ~50 min
A/B Test for Ranking Model ValueEasy

Use a two-proportion z-test to determine whether a new ranking model significantly improves recommendation CTR in an A/B test.

ExperimentationStatistical SignificanceA/B TestingBarclays
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6
A/B Testing & Experimentation5 questions · ~42 min
When to Use BanditsHard

Decide whether a multi-armed bandit is appropriate for a growth experiment versus a fixed-horizon A/B/n test.

Multi-Armed BanditsExperimentationGuardrail MetricsBarclays
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7
More topics13 questions · ~108 min
Define Metrics for New FeaturesMedium

Define a success metric for a new feature that captures real user value, not just raw usage.

MetricsFeature Prioritizationuser valueBarclays
Vanity vs Actionable MetricsEasy

Distinguish vanity metrics from metrics that drive decisions in a growth review.

North Star MetricKPIsDiagnosisBarclays
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The finish line: interview-readyComplete all 50 questions plus 2 hands-on drills to finish this plan.