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Covermymeds Data Scientist Interview Questions

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

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~3htotal time
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1
Machine LearningStart here. 3 questions · ~24 min
Feature Selection TechniquesHard

Compare filter, wrapper, and embedded feature selection methods while preserving validation performance and interpretability.

Cross-Validationmodel selectionFeature EngineeringCovermymeds
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2
A/B Testing & Experimentation3 questions · ~24 min
Discovery UI Metrics and GuardrailsMedium

Define primary and guardrail metrics for a discovery UI test, with power, MDE, and a pre-registered analysis plan.

ExperimentationGuardrail MetricsA/B TestingCovermymeds
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 TestingCovermymeds
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3
SQL & Data Manipulation3 questions + 3 drills · ~54 min
Month-Over-Month with Window FunctionsMedium

Tests your SQL window function fluency for analyzing time-based business metrics.

Window FunctionsLag/LeadRunning TotalsCovermymeds
SQL for Operational PerformanceMedium
Practice
Practice drill

Use joins, conditional aggregation, and date filtering to measure Carvana location performance over the last 30 days.

Date FunctionsGroup ByAggregationsCarvanaGeorgetown UniversityPluralsight
Top Credit Score Applicants by StateMedium
Practice
Practice drill

Identify the highest-credit-score 5% of applicants within each state using percentiles and window ranking.

Window FunctionsJoinsRankingAmerican Credit Acceptance
Consecutive Monthly Purchases SQLMedium
Practice
Practice drill

Identify Goldman Sachs customers with purchases in consecutive calendar months using month normalization and LAG.

Window FunctionsSubqueriesLag/LeadGoldman Sachs
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4
Behavioral & Leadership9 questions · ~72 min
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5
More topics6 questions · ~48 min
Prioritize Competing User RequestsMedium

Approach for deciding which user problem to solve first when multiple requests compete.

Feature PrioritizationUser NeedsProduct VisionCovermymeds
Evaluate Regression with RMSE and MAEEasy

Explain how to evaluate a regression model with RMSE and MAE, and how to interpret the tradeoff between average and large errors.

RegressionMAERMSECovermymeds
Diagnose a Metric Drop After LaunchMedium

Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.

Lagging IndicatorsLeading IndicatorsDiagnosisCovermymeds
Testing Conversion Rate ChangesEasy

Tests hypothesis testing and statistical significance reasoning for conversion metrics.

Hypothesis TestingStatistical SignificanceP-ValuesCovermymeds
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The finish line: interview-readyComplete all 24 questions plus 3 hands-on drills to finish this plan.