Data Scientist - Commodities

A leading commodity trading house is seeking an exceptional data scientist to develop sophisticated real-time market forecasting models that drive trading decisions.

You'll work on power market modelling across multiple time horizons, building production systems used daily by traders in electricity, gas, and related commodity markets. These aren't academic prototypes. You'll build live systems with real-time execution, mission-critical reliability and high-stakes impact. Prediction errors directly affect P&L and trading performance.

Responsibilities:

• Build production forecasting models for power markets that support real-time, high-value trading decisions.
• Develop mathematical optimisation and machine learning solutions combining multiple techniques for maximum accuracy.
• Design and maintain robust trading systems with real-time data processing and automated model updates.

Essential requirements:

• Several years' experience in energy forecasting or algorithmic trading within power markets.
• Strong mathematical optimisation, machine learning, and statistical modelling background.
• Production-level programming (Python, Java, C#).
• Experience with power market fundamentals and trading strategies.
• System architecture and platform development experience.
• Commercial awareness and stakeholder management.

Highly valued:

• Experience with power markets (day-ahead, intraday).
• Stochastic programming and optimization solvers.
• Time series forecasting and ensemble methods.
• Energy trading environment exposure.

You're likely someone who has:

• Built forecasting models for power markets at a trading house, utility, or energy consultancy.
• Moved beyond pure research into production system development.
• Strong technical skills and a clear understanding of the business impact.

This is a high impact front-office role with real-time decision-making responsibility.

For a confidential discussion, please get in touch or apply with your CV.