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Updated weekly · Last refresh Aug 30

Sun Life Data Scientist Interview Questions

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

38questions
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1
Machine LearningStart here. 9 questions · ~73 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 TradeoffSun Life
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2
Statistics & Probability4 questions · ~32 min
A/B Testing for Product FeaturesMedium

Explain how to design and evaluate an A/B test for a product feature, including metrics, MDE, sample size, and guardrails.

Hypothesis TestingStatistical SignificanceA/B TestingSun Life
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3
SQL & Data Manipulation5 questions + 3 drills · ~71 min
Clean and Preprocess DataEasy

Tests data cleaning, preprocessing choices, and practical handling of messy data.

Data WranglingETLQualitySun Life
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
Second Attempt Score Per UserEasy
Practice
Practice drill

Use ROW_NUMBER to return each student's second score on a specified Khan Academy exercise.

Data Analysissqluser engagementKhan Academy
Handle Missing Financial Input ValuesMedium
Practice
Practice drill

Use joins, CTEs, and CASE logic to flag and fill missing financial fields for Qlik planning records.

Data WranglingETLQualityQlik
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4
Metrics5 questions · ~41 min
Track Wellness Rewards KPIsMedium

Evaluates your skill in selecting KPIs aligned to program goals at Sun Life.

KPI developmentuser engagementSun Life
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5
A/B Testing & Experimentation4 questions · ~32 min
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6
Behavioral & Leadership6 questions · ~49 min
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7
More topics5 questions · ~41 min
Choosing Classification Evaluation MetricsEasy

Explain which classification metrics to use and how metric choice depends on the business objective and error tradeoffs.

PrecisionAccuracyRecallSun Life
Classify Customer Feedback SentimentMedium

Build a sentiment classifier for customer feedback using modern text preprocessing and transformer fine-tuning.

Text ClassificationSentiment AnalysisTokenizationSun Life
Cloud for Data PipelinesEasy

Tests tradeoffs and benefits of cloud architectures for scalable data workflows.

InfrastructureToolsQualitySun Life
Launch Personalized Supplemental Insurance FeatureMedium

Tests your product analytics judgment for deciding on a Sun Life feature launch.

feature evaluationUser Needsproduct decisionSun Life
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The finish line: interview-readyComplete all 38 questions plus 3 hands-on drills to finish this plan.