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MD Anderson Cancer Center Interview Questions

The questions to prepare for MD Anderson Cancer Center interviews, across all roles. Questions from real interview reports rank first. Updated weekly.

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1
Machine LearningStart here. 8 questions · ~67 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 TradeoffMD Anderson Cancer Center
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2
Execution8 questions · ~67 min
Resolve Conflicting Stakeholder PrioritiesMedium

Explain how you align stakeholders with competing priorities, make trade-offs explicit, and keep execution on track.

Trade-offsRisk AssessmentScope ManagementMD Anderson Cancer Center
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3
System Design4 questions · ~33 min
Deploy a Cloud ML Inference SystemMedium

Design a cloud ML deployment system for a security product, covering training, serving, updates, and production monitoring.

InfrastructureFeature DriftModel ServingMD Anderson Cancer Center
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4
Product Sense4 questions · ~33 min
Motivation in Healthcare Product WorkEasy

Explain what drives your work and how you connect motivation to meaningful user and patient impact in healthcare.

User NeedsValue PropositionUse CasesMD Anderson Cancer Center
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5
Metrics4 questions · ~33 min
Track SaaS KPI Dashboard HealthEasy

Define and track SaaS KPIs across SQL, Excel, and BI tools, then diagnose falling conversion and rising churn.

KPIsLeading IndicatorsDiagnosisMD Anderson Cancer Center
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6
SQL & Data Manipulation4 questions + 3 drills · ~63 min
Top Customers by Net SalesMedium
Practice
Practice drill

Compute top 10 customers by net sales using joins and aggregations, ordering by revenue with deterministic tie-breaking.

SubqueriesJoinsData WranglingGain DigitalTCSZest AI
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
SQL Expected vs Actual ComparisonHard
Practice
Practice drill

Compare expected and actual 6sense QA results using a FULL OUTER JOIN, aggregation, NULL-safe comparisons, and CASE status logic.

SubqueriesJoinsData Wrangling6senseApex Systems
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7
More topics18 questions · ~150 min
Linear Regression From ScratchMedium
Practice

Fit a univariate linear regression model from data using gradient descent or the normal equation.

MathArraysGradient DescentMD Anderson Cancer Center
Tell Me About YourselfEasy

Tests your ability to deliver a clear, relevant introduction tailored to the role at Aqr.

Competitive AnalysisGo-to-MarketMD Anderson Cancer Center
Data Governance in AI PipelinesMedium

Approach for governing data across AI pipelines, from ingestion and transformation to access control, quality checks, and auditability.

InfrastructureData ModelingQualityMD Anderson Cancer Center
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