We're partnering with a leading energy trading organisation to recruit a talentedMachine Learning Quant/Data Scientist to join its growing Analytics team. This is an exciting opportunity for an early-career professional 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.

The Role

As a Machine Learning Quant/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

1. Develop and improve forecasting models for energy markets, including power and gas.
2. Apply machine learning and statistical techniques to predict prices, demand and other key market variables.
3. Analyse large datasets from market, weather, generation and trading sources to identify predictive patterns.

You'll ideally have:

1. A PhD in Computer Science, Machine Learning, Data Science or another highly quantitative discipline.
2. 1–3 years' commercial experience as a Data Scientist, Machine Learning Engineer or Quantitative Analyst.
3. Experience developing forecasting or predictive models using machine learning techniques.
4. Strong Python programming skills and experience with common data science libraries such as Pandas, NumPy and Scikit-learn.
5. A solid understanding of statistics, time-series analysis and predictive modelling.