Commodity Modelling Quant
A leading commodities firm is looking to hire a Commodity Modelling Quant to develop and enhance quantitative models used across trading, risk management, and investment activities. Working closely with traders, researchers, and portfolio managers, the successful candidate will be responsible for building robust forecasting, valuation, and optimisation models across global commodity markets.
This is a highly quantitative role suited to candidates with strong modelling experience and a genuine interest in commodities markets.
Key Responsibilities
- Develop and maintain quantitative models for commodities including power, gas, oil, metals, agricultural products, and environmental markets.
- Build forecast models for prices, supply, demand, inventory levels, weather impacts, and market fundamentals.
- Research and implement statistical, stochastic, and machine learning techniques to improve forecasting accuracy.
- Develop valuation and risk models for physical and financial commodity exposures.
- Partner closely with trading teams to translate market views into robust analytical frameworks.
- Conduct scenario analysis and stress testing across commodity portfolios.
- Build production-quality research and analytics platforms in Python.
- Analyse large and alternative datasets to generate actionable market insights.
- Support the ongoing enhancement of quantitative infrastructure and modelling frameworks.
Required Background
- Advanced degree in Mathematics, Physics, Engineering, Statistics, Computer Science, Econometrics, or another quantitative discipline.
- Strong experience developing quantitative models within commodities, energy markets, financial markets, or a related field.
- Excellent Python programming skills.
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