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Updated weekly · Last refresh Oct 6

Marathon petroleum Data Analyst Interview Questions

The questions to prepare for a Marathon petroleum Data Analyst interview. Questions from real interview reports rank first. Updated daily.

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1
Behavioral & LeadershipStart here. 4 questions · ~32 min
Handling Pushback on Data InsightsMedium

Tests stakeholder management and communication when data insights are challenged, including how you respond to feedback and drive alignment.

Influence Without AuthorityStakeholder ManagementCommunicationMarathon petroleum
Prioritizing Across Competing ProjectsMedium

Tests prioritization under pressure across multiple projects, including time management, stakeholder communication, and ownership of trade-offs.

time managementmultitaskingPrioritizationMarathon petroleum
Explaining a Technical Concept ClearlyEasy

Tests communication, ownership, and stakeholder management when translating technical complexity into actionable business understanding.

Problem SolvingData Structurestechnical fundamentalsMarathon petroleum
Ensuring Visualization AccuracyMedium

Assesses how you validate and communicate insights to non-technical stakeholders.

Communicationdata visualizationMarathon petroleum
2
More topics2 questions · ~16 min
Forecasting Market TrendsMedium

Evaluates your forecasting methods for market and demand signals relevant to Marathon Petroleum.

Forecastingmarket analysisMarathon petroleum
Handling Missing Data in ModelsMedium

Tests your data preprocessing judgment for reliable predictive modeling.

predictive modelingdata cleaningMarathon petroleum

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
SQL Grouping and OrderingMedium
Practice
Practice drill

Aggregate transaction counts and volumes by terminal and day, then sort results by the busiest terminal-day combinations.

Date FunctionsGroup ByAggregationsMarathon petroleum
Handling Missing DataEasy
Practice
Practice drill

Replace missing sales fields with defined defaults and return a consistently ordered dataset.

missing valuesdata cleaningnull handlingUniversity of MinnesotaThe Home DepotNationwide
Handling Missing DataMedium
Practice
Practice drill

Standardize missing observation fields with fallback values, missingness flags, and ordered output.

Window Functionsmissing valuesdata cleaningEversource EnergyCincinnati Children's HospitalAdtalem Global Education
The finish line: interview-readyComplete all 6 questions plus 3 hands-on drills to finish this plan.