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Eli Lilly and Data Scientist Interview Questions

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

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~5htotal time
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1
Statistics & ProbabilityStart here. 4 questions · ~33 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-ValuesEli Lilly and
Interpreting P Values in TestingEasy

Explain what a p-value means in hypothesis testing and how it relates to statistical significance.

Hypothesis TestingStatistical SignificanceP-ValuesEli Lilly and
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2
Machine Learning8 questions · ~66 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 TradeoffEli Lilly and
Handling Missing Values in MLEasy

Explain practical strategies for handling missing values in a supervised learning workflow, from diagnosis to modeling and validation.

Cross-ValidationFeature EngineeringRegularizationEli Lilly and
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3
Metrics3 questions · ~25 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 IndicatorsDiagnosisEli Lilly and
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4
A/B Testing & Experimentation3 questions · ~25 min
Avoid Pitfalls in Online ExperimentsHard

Explain common online experimentation pitfalls and how to design, analyze, and decide in ways that avoid false wins.

Network InterferenceNovelty EffectSample Ratio MismatchEli Lilly and
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5
Behavioral & Leadership16 questions · ~131 min
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6
More topics3 questions · ~25 min
SQL Rolling Average by CityMedium

Tests SQL window function proficiency for time-series aggregation and grouping logic.

Window FunctionsDate FunctionsRunning TotalsEli Lilly and
Drug Marketing Strategy OptimizationMedium

Tests product sense and data-driven thinking for improving marketing outcomes at Eli Lilly and.

Feature PrioritizationUser NeedsProduct VisionEli Lilly and
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Window Functions SQL QueryMedium
Practice
Practice drill

Rank Eli Lilly products by regional completed prescription revenue using aggregation, joins, a CTE, and RANK().

Window FunctionsRankingRunning TotalsEli Lilly and
Active Customer List by CityEasy
Practice
Practice drill

Retrieve active customers from a single table, grouped by city with a customer count and sorted by highest count.

JoinsData WranglingAggregationsEli Lilly and
Analyze Decision Impact by RegionEasy
Practice
Practice drill

Use joins, CASE WHEN, and date filtering to compare outcome rates before and after a decision.

Data WranglingDiagnosisAggregationsHarbourVest Partners
The finish line: interview-readyComplete all 37 questions plus 3 hands-on drills to finish this plan.