Quantitative Power Analyst (Data Scientist)
Short Term Intraday Stack Models
Power Trading
London
We are working with one of the UK’s leading power generation companies - generating 10–15% of the UK’s electricity - with sites across the UK, Ireland, and Germany. As they scale from 3.5 GW to 7 GW of generation and add 500 MW of battery storage, they're building out their data science capability on the trading floor.
We are seeking a highly motivated Quantitative Power Analyst to join our trading team. This role is focused on short-term power markets and sits at the intersection of trading, quantitative analysis, and data-driven modelling.
Top Three Focus Areas
* Developing algorithms for asset optimisation in short-term power markets.
* Applying short-term power trading expertise to drive trading desk performance.
* Building and improving short-term pricing models (e.g., stack models, scratch models).
What you'll be doing
* Take ownership over existing models, and building new short-term intraday stack models
* Own and enhance short-term stack forecasting and dispatch models
* Developing algorithms for optimising assets in the short-term power market, including dispatch/stack models used for pricing and trading decisions
* Working directly with the trading desk to support short-term power trading strategies and decisions, ensuring models are commercially relevant and impactful.
* Build intraday trading tools and collaborate on automated strategies
* Apply time series and fundamentals-based modelling to support trading decisions
* Work alongside data engineers to deploy production-grade code
* Mentor others and help embed data science best practices across the team
What we're looking for
* Strong quantitative background; Master’s degree in computer science, mathematics, engineering, physics, machine learning, or a related field. Ph.D. is a plus.
* Proficiency in Python and ability to write clean, production-quality code.
* 5+ years of relevant experience in short-term power trading, quant analysis, or algorithmic modelling.
* Strong experience in short-term power trading, with direct impact on trading desk decisions.
* Hands-on expertise in developing algorithms for asset optimisation in the short-term power market.
* Proven experience with stack/dispatch modelling and short-term pricing techniques.
* Experience in power markets, with knowledge of financial markets and trading concepts
* Experience with back testing techniques appropriate to financial market applications
* Experience exploring and extracting insights from heterogeneous multi-dimensional data sets, and presenting complex data visually
* Time series modelling (both machine-learning and econometric approaches)