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Updated weekly · Last refresh Nov 6
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CaixaBank Data Scientist Interview Questions

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

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~2htotal time
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1
A/B Testing & ExperimentationStart here. 5 questions · ~41 min
Design Test for New FeatureMedium

Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.

experiment designfeature evaluationA/B TestingCCaixaBank
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2
Behavioral & Leadership4 questions · ~33 min
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3
More topics8 questions · ~66 min
Validate a Model for OverfittingMedium

Explain how to validate a model and spot overfitting before it reaches production.

Hyperparameter TuningCross-ValidationBias-Variance TradeoffCCaixaBank
Common Customer Analytics MethodsMedium

Explain the main statistical methods used in customer analytics and when each is appropriate.

Confidence IntervalsRegressionHypothesis TestingCCaixaBank
Define Metrics for New FeaturesMedium

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

MetricsFeature Prioritizationuser valueCCaixaBank
Investigate User Engagement DeclineMedium

Investigate a 15% engagement decline by decomposing the metric, isolating root causes, and proposing actions.

RetentionDiagnosisEngagement MetricsCCaixaBank
Choose an ML Algorithm for ClassificationMedium

Evaluates model selection reasoning for classification tasks and trade-off awareness.

Classificationmodel selectionCCaixaBank
Steps to Ensure Analysis AccuracyMedium

Tests your validation, testing, and verification methods for analytics correctness.

Data WranglingAggregationsQualityCCaixaBank
Evaluate a Recommendation SystemMedium

Evaluate whether a recommendation system is improving engagement and ranking quality, not just offline metrics.

PrecisionAccuracyRecallCCaixaBank
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

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

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Handling Missing ValuesMedium
Practice
Practice drill

Create an auditable application dataset by applying explicit PostgreSQL rules for missing candidate, status, salary, and date values.

missing valuesdata cleaningnull handlingAircallathenahealthHays
SQL Top 10% Creators by EngagementMedium
Practice
Practice drill

Write a SQL query to identify the top 10% of creators based on engagement metrics over the last 30 days. Use the provided creators and creatorengagements ...

Date Functionssql queryData AnalysisTikTok
The finish line: interview-readyComplete all 17 questions plus 3 hands-on drills to finish this plan.