Modeling Quantitative Analyst, Cross-Asset Trading Analytics

What you will do

Develop, implement and maintain quantitative models supporting trading, risk management, valuation, and portfolio optimization across multiple energy commodities (Crude Oil, Natural Gas, Power, LNG, Freight etc …) Build analytical frameworks to evaluate market fundamentals, price formation, asset relationships, and cross-commodity trading opportunities. Conduct statistical analysis, time-series modeling, scenario analysis, and forecasting to support commercial decision-making. Develop and enhance pricing, volatility, correlation, and risk models used by trading, origination and risk management teams. Partner closely with traders and commercial teams to translate business challenges into quantitative solutions and actionable market insights. Create and maintain analytical tools, dashboards, and model infrastructure to improve trading efficiency and decision support. Analyze market behavior and emerging trends across energy, environmental products, freight, foreign exchange, and related financial markets. Evaluate model performance, conduct back-testing, and implement model enhancements to improve predictive accuracy and commercial value. Collaborate with technology teams to deploy robust, scalable, and production-ready quantitative solutions. Communicate complex analytical findings and model outputs to commercial stakeholders in a clear and concise manner. Contribute to the development of quantitative best practices, analytical methodologies, and model governance standards across the organization. What you bring Master's, or PhD degree in Applied Mathematics, Statistics, Financial Engineering, Physics, Computer Science, Operations Research or a related quantitative discipline. Strong quantitative and analytical problem-solving skills with the ability to develop practical solutions to complex commercial challenges. Experience developing quantitative models in commodities or other asset classes either in energy companies, hedge funds or banks. Strong understanding of probability, stochastic calculus, statistics, optimization techniques and machine learning methodologies. Experience working with large and complex datasets to generate actionable business insights. Proficiency in Python ideally or other programming languages such as C++, C#, C or Java. Experience with quantitative analytics libraries and data science toolsets. Knowledge of market risk concepts, valuation methodologies, portfolio analytics, and trading performance measurement. Experience with model validation, back-testing, and analytical governance frameworks. Ability to communicate technical concepts effectively to both quantitative and non-quantitative stakeholders. Demonstrated ability to work collaboratively in a fast-paced commercial environment while managing multiple priorities.

Preferred Qualifications

Advanced degree in a quantitative field. Experience supporting commodity trading, energy markets, environmental products, or financial trading organizations. Experience with derivative pricing, stochastic calculus, Monte Carlo simulation, PDEs, stochastic optimal control and optimization techniques. Knowledge of power, natural gas, crude oil, refined products, LNG, biofuels, carbon markets, freight, or foreign exchange markets. Experience with cloud-based analytics platforms, distributed computing environments, and modern data architectures. Familiarity with software engineering best practices including version control, testing, and model deployment. Your benefits An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life. We offer you: Pension Plan: Enrollment is automatic and at no cost to you. The basic benefit is a monthly annuity to be paid to you in ret