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Updated weekly · Last refresh Oct 17

AXA Data Scientist Interview Questions

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

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1
Machine LearningStart here. 9 questions · ~73 min
Detect Rare Payment FraudMedium

Build an imbalanced binary classifier for payment fraud detection using cost-sensitive learning, threshold tuning, and precision-recall evaluation.

Cross-ValidationFeature EngineeringSupervised LearningAXA
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2
Behavioral & Leadership9 questions · ~73 min
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3
More topics10 questions · ~81 min
Statistical Significance in Business DecisionsEasy

Explain what statistical significance means, how p-values and confidence intervals support decisions, and why significance alone is not enough.

Hypothesis TestingStatistical SignificanceP-ValuesAXA
Optimizing Large Transaction Table JoinsHard

Explain how to tune a slow PostgreSQL query that joins several large transaction tables using indexes, join strategy, and partitioning.

JoinsperformancesqlAXA
Diagnose KPI Drop After ReleaseMedium

Diagnose a post-release KPI drop by separating instrumentation issues from real behavior changes and tracing the problem through the metric hierarchy.

KPILeading IndicatorsDiagnosisAXA
Pitfalls in Insurance ExperimentsHard

Tests ability to anticipate and mitigate threats to validity in customer-facing insurance experiments.

Network InterferenceNovelty EffectSample Ratio MismatchAXA
Telemetry Data Pipeline DesignMedium

Tests data engineering design for reliable ingestion, cleaning, and storage of high-volume telemetry.

Data QualityETLBatch ProcessingAXA
Define Product Metrics for Fraud or Self-ServiceMedium

Tests product sense and metric design tied to fraud and customer experience outcomes at AXA.

MetricsUse CasesProduct VisionAXA
Parse Claims Text in PythonMedium

Tests practical Python skills for text cleaning and feature-ready parsing from claims data.

data preprocessingText ClassificationTokenizationAXA
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Handling Missing DataMedium
Practice
Practice drill

Standardize missing observation fields with fallback values, missingness flags, and ordered output.

Window Functionsmissing valuesdata cleaningEversource EnergyCincinnati Children's HospitalAdtalem Global Education
Scenario-Based Business CaseHard
Practice
Practice drill

Aggregate project outcomes and present a defensible SQL-based business case analysis.

project experienceJoinsbusiness problemTikTok
Rolling Average Payroll VolumeMedium
Practice
Practice drill

Calculate Gusto payroll submission volume and its 7-day rolling average for each active business category.

Window FunctionsDate FunctionsJoinsGusto
The finish line: interview-readyComplete all 28 questions plus 3 hands-on drills to finish this plan.