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Quantitative Analytics Manager

Job in San Antonio, Bexar County, Texas, 78208, USA
Listing for: Marathon Petroleum Corporation
Full Time position
Listed on 2026-01-12
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst
  • Finance & Banking
    Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Overview

Quantitative Analytics Manager at Marathon Petroleum Corporation. The role leads a team of quantitative analysts responsible for advanced analytical tools and market insights to inform trading strategies across commercial activities.

At MPC, we’re committed to being a great place to work — welcoming new ideas, encouraging diverse perspectives, developing our people, and fostering a collaborative team environment.

Key Responsibilities
  • Lead and mentor a team of quantitative analysts supporting front-line commercial and trading teams.
  • Translate commercial objectives into clear analytical roadmaps, prioritizing projects based on value, feasibility, and business impact.
  • Partner with fundamental analytics, trading, origination, risk, IT and other internal teams to identify opportunities for analytical innovation.
  • Provide real-time analytical support and insight for commercial negotiations, deal structuring, asset optimization, and risk management.
  • Champion adoption of new analytical technologies, frameworks, and tools.
  • Design and validate statistical, econometric, and machine learning models to enhance market understanding and commercial performance.
  • Ensure rigorous model governance, documentation, version control, and performance monitoring.
Education and Experience
  • Bachelor’s degree in a quantitative field (e.g., Applied Mathematics, Statistics, Engineering, Quantitative Finance, etc.) required; advanced degree preferred.
  • Eight (8) years of experience in trading analytics, quantitative research, or commercial decision support in energy or commodity markets.
Preferred Skills
  • Proficiency in Python, SQL, and modern data-science toolkits; experience with cloud environments (AWS, Azure, or GCP).
  • Deep understanding of energy commodity market fundamentals.
  • Experience with derivative pricing, stochastic modeling, time-series forecasting, or optimization techniques (e.g., linear/mixed-integer).
  • Strong communication skills and ability to translate complex statistics into business outcomes.
  • Curiosity, creativity, and continuous improvement mindset.
Location

Houston, TX

Relocation

Available

Estimated Travel
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