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Activision Blizzard Data Scientist Interview Questions

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

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1
Machine LearningStart here. 4 questions · ~32 min
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffActivision Blizzard
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2
Statistics & Probability3 questions · ~24 min
Testing Retention SignificanceMedium

Tests hypothesis testing and experimental thinking for retention changes.

Confidence IntervalsHypothesis TestingStatistical SignificanceActivision Blizzard
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3
Behavioral & Leadership8 questions · ~64 min
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4
More topics6 questions · ~48 min
Primary vs Guardrail Metric ChoiceMedium

Choose a primary success metric and guardrails for a game experiment, then explain how that choice drives power, analysis, and ship decisions.

ExperimentationGuardrail MetricsA/B TestingActivision Blizzard
Define Metrics for New FeaturesMedium

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

MetricsFeature Prioritizationuser valueActivision Blizzard
Reducing Churn for a GameMedium

Tests your end-to-end churn analysis process and prioritization of drivers.

RetentionChurnDiagnosisActivision Blizzard
SQL Window Functions for RetentionMedium

Tests SQL proficiency for time-based cohort and retention analysis.

Window FunctionsDate FunctionsRunning TotalsActivision Blizzard
Diagnosing a Drop in Key MetricsMedium

Tests your debugging mindset for metrics, instrumentation, and causal investigation.

North Star MetricLeading IndicatorsDiagnosisActivision Blizzard
Behavior Analysis to Improve RetentionMedium

Tests your product analytics approach and ability to turn behavior data into retention improvements.

User NeedsUse CasesProduct VisionActivision Blizzard

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
7-Day Rolling Active UsersMedium
Practice
Practice drill

Compute daily active users and a 7-day rolling average using a CTE, distinct counts, and window functions.

Window FunctionsDate FunctionsRunning TotalsMetaSpotifyMeta IT
Customer Transaction Running TotalsEasy
Practice
Practice drill

Calculate each customer's cumulative transaction amount over time using a CTE and window function.

Window FunctionsDate FunctionsRunning TotalsBanco SantanderAnzBank Of Tokyo-Mitsubishi UFJ
Rolling 7-Day System Error AverageMedium
Practice
Practice drill

Calculate a rolling 7-day average of system error counts using window functions and date-based aggregation.

Window FunctionsDate FunctionsRunning TotalsDatadogToyotaAgile Defense
The finish line: interview-readyComplete all 21 questions plus 3 hands-on drills to finish this plan.