Quant Trading Strategist - Crude, Products, and Freight

About us

At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.

We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together.

What role you will play on your team

Join a high performing Front Office Point of View Trading Quant team focused on generating, testing and delivering robust trading signals indicators for the Crude and Refined Products markets. You will apply statistical modelling, machine learning, quantitative research and market microstructure intuition to uncover predictive patterns and convert them into actionable insights for traders.

Your work will directly support the trading desk by informing discretionary and systematic decision making, accelerating idea generation, and enhancing strategy robustness. You will also contribute to global initiatives aimed at advancing systematic and ML driven analytics within Global Trading.

This role is located in Singapore.

What you will do

• Generate and research strategies for crude and products markets using statistical methods, machine learning, feature engineering and quantitative modelling.

• Work closely with traders to translate market intuition into testable hypotheses, validate signal behaviour and improve decision making across short term and medium term horizons.

• Analyse large volumes of market, fundamental and alternative data to identify patterns, anomalies and structural behaviours relevant to Crude & Products trading.

• Build and maintain robust back testing frameworks, evaluate strategy performance, stress test signals and ensure statistical validity across regimes.

• Develop scalable research tooling and systematic strategy components using Python and modern data science libraries.

• Contribute signal and modelling insight to broader systematic and data driven initiatives across the trading organization.

• Monitor live strategy behaviour, support execution logic improvements, and partner with developers to deploy production ready analytics.

What you bring

• Strong quantitative background (MSc/PhD preferred) in applied math, statistics, econometrics, data science, computer science or similar fields.

• Expertise in statistical modelling, machine learning, predictive analytics, feature engineering and time series methods applied to financial or commodity markets.

• Advanced Python skills for research, modelling and data processing; experience with ML libraries (scikit learn, PyTorch, TensorFlow) is a plus.

• Ability to analyse large datasets, uncover signal patterns and communicate findings clearly to traders and commercial teams.

• Experience building and validating back tests, including performance attribution, robustness checks and sensitivity analysis.

• Curiosity about market structure, pattern discovery and quantitative alpha generation in commodity futures and spreads.

• A proactive, research driven mindset with strong documentation habits and attention to statistical integrity.

Your benefits

An ExxonMobil career is one designed to last and we provide job rotations throughout your career with us. 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. Currently our employees' benefits include long term savings allowance, dental reimbursement, annual health checkups and home ownership assistance plan amongst others and these are updated from time to time.

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