Data Scientist - Energy Trading

We're partnering with a leading energy trading organisation to recruit a talented Data Scientist to join its growing Analytics team. This is an exciting opportunity for an early-career Data Scientist with a strong academic background and a passion for applying machine learning to real-world energy markets. Working alongside experienced Data Scientists, Quantitative Analysts and Traders, you'll help develop forecasting models that support trading decisions across power, gas and other energy markets. If you're looking to combine advanced analytics with a fast-paced commercial environment, this role offers the chance to work on challenging problems with direct business impact. The Role As a Data Scientist, you'll contribute to the development and enhancement of forecasting models using machine learning and statistical techniques. You'll analyse complex datasets, identify market signals and help deliver predictive insights that support Front Office trading activity. You'll work collaboratively across Trading, Quantitative Analytics and Technology teams, gaining exposure to both the technical and commercial aspects of energy trading. Key Responsibilities * Develop and improve forecasting models for energy markets, including power and gas. * Apply machine learning and statistical techniques to predict prices, demand and other key market variables. * Analyse large datasets from market, weather, generation and trading sources to identify predictive patterns. * Support the design, testing and validation of forecasting models. * Build and maintain data pipelines to support model development and deployment. * Collaborate with Traders and Quantitative Analysts to understand business requirements and translate them into analytical solutions. * Monitor model performance and recommend enhancements. * Present findings and insights to both technical and non-technical stakeholders. * Keep up to date with developments in machine learning and forecasting methodologies. About You We're looking for someone with a strong quantitative background who enjoys solving complex problems and wants to build a career in energy trading analytics. You'll ideally have: * A PhD in Mathematics, Statistics, Physics, Computer Science, Machine Learning, Data Science or another highly quantitative discipline. * 1–3 years' commercial experience as a Data Scientist, Machine Learning Engineer or Quantitative Analyst. * Experience developing forecasting or predictive models using machine learning techniques. * Strong Python programming skills and experience with common data science libraries such as Pandas, NumPy and Scikit-learn. * Experience working with SQL and large datasets. * A solid understanding of statistics, time-series analysis and predictive modelling. * Strong problem-solving and analytical skills. * Excellent communication skills and the ability to explain technical concepts clearly. Desirable Experience * Exposure to energy markets, commodities or financial markets. * Experience with time-series forecasting techniques. * Knowledge of cloud platforms or distributed computing. * Familiarity with TensorFlow, PyTorch or similar machine learning frameworks. * Experience using Git and software development best practices.