Top 39
Prep plan
Updated weekly · Last refresh Aug 30

Tinder Data Scientist Interview Questions

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

39questions
~6htotal time
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1
SQL & Data ManipulationStart here. 4 questions · ~37 min
Rolling 7-Day Swipes AverageMedium
Practice

Calculate each Tinder user's rolling 7-day swipe average using daily aggregation and a date-based window frame.

Window FunctionsDate FunctionsRunning TotalsTinder
Average Swipes Last MonthEasy
Practice

Calculate Tinder's average swipes per user for the previous calendar month using a LEFT JOIN, CTE, and date filtering.

Date FunctionsGroup ByAggregationsTinder
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2
Statistics & Probability4 questions · ~37 min
Evaluating Observed Lift SignificanceMedium

Explain how to test whether an observed experiment lift is real using hypothesis testing, p-values, and confidence intervals.

Confidence IntervalsStatistical SignificanceP-ValuesTinder
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3
Machine Learning5 questions · ~46 min
Handling Missing Data in MLMedium

Explain practical strategies for handling missing data and how to validate that the chosen approach improves model performance.

Feature EngineeringData WranglingSupervised LearningTinder
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4
Metrics4 questions · ~37 min
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 IndicatorsDiagnosisTinder
Measure Retention Beyond ConversionsMedium

Assess whether campaign-driven conversions turn into retained, valuable users instead of short-lived acquisition spikes.

RetentionConversion RateDiagnosisTinder
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5
A/B Testing & Experimentation7 questions · ~65 min
Network Interference in Collaboration TestMedium

Explain when network interference threatens an A/B test, how it biases estimates, and how to redesign the experiment safely.

Network InterferenceExperimentationA/B TestingTinder
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6
Behavioral & Leadership14 questions · ~129 min
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7
More topics1 question · ~9 min
Features for RetentionMedium

Tests feature attribution thinking for retention modeling.

User NeedsUse CasesProduct VisionTinder
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