McKinsey & Data Analyst Interview Questions
The questions to prepare for a McKinsey & Data Analyst interview. Questions from real interview reports rank first. Updated daily.
Explain how to handle NULLs, skewed values, and outliers when preparing an analysis dataset using SQL.
McKinsey &Explain how to tune a slow PostgreSQL query that joins several large transaction tables using indexes, join strategy, and partitioning.
McKinsey &Standardize missing observation fields with fallback values, missingness flags, and ordered output.
Eversource Energy
Cincinnati Children's Hospital
Adtalem Global EducationBuild an efficient PostgreSQL report that aggregates partitioned project events and costs without join multiplication.
McKinsey &Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.
Identify likely delay distributions and explain how to model skew, zeros, negatives, seasonality, and extreme disruptions in shipment delays.
McKinsey &Prioritize the most useful data sources to assess competitors before entering a new market.
McKinsey &Design an A/B test for a new digital product launch with clear metrics, power, guardrails, and a defensible ship decision.
McKinsey &Tests structured root-cause analysis using transaction metrics and segmentation.
McKinsey &Tests pipeline design choices for reliability, automation, and maintainable data ingestion.
McKinsey &Explain why correlation measures association, while causation requires evidence that changing one variable changes the other.
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