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Updated weekly · Last refresh Aug 30

Sunayu Data Scientist Interview Questions

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

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1
SQL & Data ManipulationStart here. 3 questions + 3 drills · ~54 min
Joining Large Datasets for Real-Time GraphsMedium

Tests ability to design scalable SQL/data-joining strategies for real-time graph analytics.

Sunayu
Handling Missing or Noisy DataMedium

Evaluates practical data cleaning and integrity safeguards in production pipelines.

data integritySunayu
SQL Duplicate Record DetectionEasy
Practice
Practice drill

Find duplicate American Institutes for Research assessment submissions using a CTE, GROUP BY, HAVING, and joins.

deduplicationsqldata integrityAmerican Institutes for ResearchMacy's
Weekly Service KPI by TeamMedium
Practice
Practice drill

Analyze weekly service delivery performance by team using joins, a CTE, date aggregation, and KPI calculations.

KPIJoinssqlDeloitteReputation
Identify Funnel Bottlenecks in OnboardingHard
Practice
Practice drill

Use joins, CTEs, and aggregations to find the weakest step in an onboarding funnel and estimate lost conversions.

Funnel AnalysissqlDiagnosisAtlassianRevolut
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2
Statistics & Probability3 questions · ~24 min
Statistical Significance in A/B TestsMedium

Assesses ability to communicate A/B testing validity using statistical significance.

CommunicationStatistical SignificanceA/B TestingSunayu
Explain Statistical SignificanceMedium

Assesses communication skills for conveying statistical ideas to non-technical audiences.

CommunicationStatistical SignificanceSunayu
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3
A/B Testing & Experimentation3 questions · ~24 min
Experiment Design for Decision-MakingMedium

Tests experimental design skills for measuring algorithm impact on user decisions.

experiment designSunayu
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4
Behavioral & Leadership4 questions · ~32 min
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5
More topics4 questions · ~32 min
Diagnose KPI Drop After ReleaseMedium

Diagnose a post-release KPI drop by separating instrumentation issues from real behavior changes and tracing the problem through the metric hierarchy.

KPILeading IndicatorsDiagnosisSunayu
Designing Product Metrics for AIMedium

Evaluates product sense in defining metrics that reflect value from AI-driven features at Sunayu.

Sunayu
Investigating Metric DropsMedium

Evaluates structured incident investigation for metric regressions in an intelligence platform.

root cause analysisperformance metricsSunayu
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