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The Federal National Mortgage Association - Fannie Mae Data Scientist Interview Questions

The questions to prepare for a The Federal National Mortgage Association - Fannie Mae Data Scientist interview. Questions from real interview reports rank first. Updated daily.

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SQL Moving Average With WindowsMedium
Practice

Calculate each customer’s 30-day moving average of daily transaction totals using aggregation and a PostgreSQL window frame.

Data AnalysisThe Federal National Mortgage Association - Fannie Mae
Define Metrics for New FeaturesMedium

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

MetricsFeature Prioritizationuser valueThe Federal National Mortgage Association - Fannie Mae
Diagnose Loan Approval Rate DropMedium

Evaluates structured troubleshooting of business metrics using data and causal reasoning.

Data AnalysisDiagnosisThe Federal National Mortgage Association - Fannie Mae
A/B Testing Pitfalls And MitigationMedium

Assesses experience preventing bias, leakage, and invalid conclusions in experiments.

A/B TestingThe Federal National Mortgage Association - Fannie Mae
Explain Statistical SignificanceMedium

Assesses ability to translate statistical concepts into clear, stakeholder-friendly explanations.

CommunicationStatistical SignificanceThe Federal National Mortgage Association - Fannie Mae
Post-COVID Market RecoveryHard

Evaluates product sense and ability to reason about housing market dynamics using data signals.

market analysisThe Federal National Mortgage Association - Fannie Mae
SQL Latest Loan Per BorrowerMedium

Assesses SQL skills for deduplicating and selecting the latest record per entity.

sqlThe Federal National Mortgage Association - Fannie Mae
Account For Seasonality In ExperimentsMedium

Evaluates experimental design choices that control for seasonal effects in housing metrics.

experiment designseasonalityThe Federal National Mortgage Association - Fannie Mae

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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
SQL Window Functions Moving AverageMedium
Practice
Practice drill

Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.

Window FunctionsData AnalysissqlEEvalueserveSShyena Tech YarnsAATB Financial
Running Average With Window FunctionsEasy
Practice
Practice drill

Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.

Window FunctionsData AnalysissqlHingeCCatalyst Operations & AnalyticsAAlight Solutions
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