Lead Risk Quantitative Analyst

Marathon Petroleum Corporation•Findlay, OH

2d•Hybrid

About The Position

MPC has an opportunity for a Lead Risk Quantitative Analyst with a focus on building and maintaining analytical data models. This role will help develop and implement analytical models for stress testing of the Supply, Trading, & Origination portfolio and calculating portfolio risk metrics including Value at Risk (VaR), Cash Flow at Risk (CFaR), Earnings at Risk (EaR). The position will also work closely with the Risk Oversight and Performance Measurements Teams in Middle Office identify opportunities and implement enhancements to the existing oversight metrics. Middle Office is new to MPC and this is an opportunity to help shape the Middle Office relationships and process improvements. This position is open to Findlay, OH, Houston, TX, and San Antonio, TX.

Requirements

Bachelor’s degree required.
Six (6) years of experience required in analytical modeling.

Nice To Haves

Business, Accounting, Finance, Mathematics, Engineering, Economics or a related discipline preferred.
Preferred System Experience: Power BI, Monte Carlo simulation, RDW
Prefer prior experience in commercial, economics, risk oversight, or financial/analytical modeling.

Responsibilities

Develop and maintain quantitative risk models used to measure portfolio exposures, stress scenarios, and downside risk across commodity markets.
Build analytical frameworks that support enterprise risk measurement, concentration analysis, and forward-looking risk assessments.
Perform advanced risk analytics and modeling activities, including valuation modeling, exposure simulations, scenario analysis, and sensitivity testing.
Document methodologies, validate assumptions, and support ongoing model enhancements.
Support price curve and valuation processes by maintaining analytical models, validating market data inputs, performing curve analysis, and assisting with valuation methodologies for physical and financial commodity positions.
Deliver actionable risk analytics and decision-support insights by evaluating risk-return tradeoffs, portfolio impacts, and scenario outcomes for trading, origination, optimization, and strategic business initiatives.
Partner with Commercial, Risk Oversight, Finance, and Data teams to translate business challenges into quantitative solutions.
Communicate model outputs and analytical findings clearly to both technical and non-technical stakeholders.
Support model governance and analytical standards by documenting models, performing back-testing and validation activities, and ensuring transparency, accuracy, and consistency in analytical outputs.
Research and apply advanced quantitative techniques such as Monte Carlo simulation, stochastic modeling, optimization methods, volatility analysis, and machine learning approaches where appropriate to enhance risk measurement capabilities.