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Marsh & Mclennan Data Analyst Interview Questions

The questions to prepare for a Marsh & Mclennan Data Analyst interview. Questions from real interview reports rank first. Updated weekly.

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1
PipelinesStart here. 4 questions · ~32 min
Data Cleaning in ETL PipelinesEasy

Approach for cleaning and preparing raw data inside an ETL pipeline.

Data WranglingETLQualityMarsh & Mclennan
Large Dataset Analysis PipelineEasy

Discuss a large-scale data analysis project with focus on the pipeline, tooling, and data quality approach.

ToolsData ModelingQualityMarsh & Mclennan
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2
Behavioral & Leadership30 questions · ~240 min
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3
More topics7 questions · ~56 min
Evaluate a New Marketing InitiativeMedium

Design an experiment to test whether a new marketing initiative improves conversion without harming key guardrails.

ExperimentationStatistical SignificanceA/B TestingMarsh & Mclennan
SQL Query With ConditionsEasy

Tests SQL fundamentals and ability to filter and retrieve relevant data.

SubqueriesJoinsData WranglingMarsh & Mclennan
Find a Data TrendMedium

Tests your analytical thinking and ability to translate insights into results.

KPILeading IndicatorsDiagnosisMarsh & Mclennan
Linear Regression ImplementationMedium

Tests your understanding of model setup, training, and evaluation basics.

RegressionCorrelationVarianceMarsh & Mclennan
Why Ness Digital EngineeringEasy

Tests motivation and fit for Ness Digital Engineering's digital engineering environment.

Value PropositionProduct VisionMarsh & Mclennan
Optimize a Slow QueryHard

Tests SQL performance tuning skills and ability to diagnose bottlenecks.

JoinsData WranglingCTEsMarsh & Mclennan
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
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
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
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
The finish line: interview-readyComplete all 41 questions plus 3 hands-on drills to finish this plan.