Senior Data Scientist - Commodity Trading and Risk Management

About the role

Develop and improve data science models and tools for commodity price forecasting, hedging, and risk management, including backtesting strategies and tailoring machine-learning solutions to client risk appetites and constraints. Advise clients and collaborate with their teams and internal engineers to deliver insights, build lasting analytical capabilities, and support adoption of improved decision-making models. Requires an undergraduate degree, production-quality Python skills for model development, and experience applying advanced analytics and statistical methods to business problems involving commodity markets. Candidates should be able to explain market nuances and analytical results to executive audiences; preferred qualifications include quantitative postgraduate education, commodity-market experience, and expertise in relevant modeling, optimization, LLM, and CTRM/ETRM workflows.