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Updated weekly · Last refresh Oct 17

Simon-Kucher Data Scientist Interview Questions

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

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1
SQL & Data ManipulationStart here. 4 questions + 2 drills · ~54 min
Monthly Sales Trends by CategoryMedium
Practice

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingSimon-Kucher
SQL Window Functions ExperienceMedium
Practice
Practice drill

Use SQL window functions to rank regions by average 2024 yield within each country.

Window FunctionsJoinsData ManipulationErnst & YoungKBRMaximus Tech
Window Functions for TrendsMedium
Practice
Practice drill

Calculate account-level running totals and three-row moving averages with PostgreSQL window functions.

Window FunctionsJoinsData ManipulationAAxtriaGGrowth IntelligenceGGrupo Astek
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2
Machine Learning4 questions · ~34 min
Random Forests and Feature ImportanceMedium

Tests understanding of ensemble methods and interpretation of feature importance signals.

Ensemble MethodsDecision TreesSimon-Kucher
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3
Statistics & Probability3 questions · ~25 min
Estimating Willingness to PayMedium

Tests methods for deriving WTP from observed purchase behavior and sales transactions.

pricingRegressionSimon-Kucher
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4
Behavioral & Leadership11 questions · ~93 min
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5
More topics6 questions · ~51 min
Calculate Customer Lifetime ValueMedium

Walk through the math of customer lifetime value using retention, churn, and margin assumptions.

CACRetentionLTVSimon-Kucher
Define Metrics for a Customer TestHard

Define the primary metric, guardrails, and power for a customer-facing A/B test before deciding whether to ship.

ExperimentationGuardrail MetricsA/B TestingSimon-Kucher
Designing a Marketing Mix ModelHard

Tests ability to build MMM for channel budget optimization and causal attribution.

user valueSimon-Kucher
Python Missing Value ImputationMedium

Tests data cleaning, imputation choices, and pipeline readiness for ML modeling.

Data QualityData WranglingAutomationSimon-Kucher
Diagnose Conversion Drop Post LaunchMedium

Diagnose why conversion fell from 4.8% to 3.1% after a launch by breaking the metric across funnel steps, cohorts, and segments.

Funnel AnalysisConversion RateDiagnosisSimon-Kucher
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The finish line: interview-readyComplete all 28 questions plus 2 hands-on drills to finish this plan.