Data Scientist – Energy Forecasting

ImpacT Hire is supporting one of our clients – an established energy group with a growing portfolio of assets across renewable energy, battery storage, and e-mobility.
The company is currently building a new AI-driven energy management platform from the ground up, designed to improve how energy assets are forecasted and optimized. The project combines the dynamics and ownership of a start-up environment with the backing and real-world assets of an established energy business.

We are looking for a Senior Data Scientist with strong forecasting experience who will take ownership of developing production-grade forecasting models used for energy asset optimization and decision-making. The initial focus will be on electricity price forecasting across day-ahead, intraday, and balancing markets, with the opportunity to expand into additional renewable and energy assets over time.

Responsibilities:
➢ Design, develop, and continuously improve forecasting models using statistical, Machine Learning, and hybrid approaches;
➢ Build price forecasts for day-ahead, intraday, and balancing energy markets;
➢ Develop models for system direction, imbalance, and other short-term energy market dynamics;
➢ Build probabilistic forecasting outputs, including quantiles, distributions, and scenarios;
➢ Take models through the full lifecycle – from experimentation and prototyping to production deployment and continuous improvement;
➢ Perform rigorous backtesting, walk-forward validation, and live model performance monitoring;
➢ Develop and improve retraining pipelines as models and energy assets move into production;
➢ Work closely with optimization and trading specialists to ensure forecasting outputs can be effectively consumed by optimization models;
➢ Contribute to the evolution of the wider AI/ML platform as the solution expands across battery storage, solar, wind, and other energy assets.

Requirements:
➢ 4+ years of hands-on experience in Data Science, Machine Learning, quantitative modelling, or a closely related field;
➢ Strong practical experience with forecasting and time-series modelling – this is a key requirement for the role;
➢ Proven experience developing forecasting models beyond the prototype stage, ideally taking them into production;
➢ Strong Python skills, including experience with pandas, NumPy, scikit-learn, gradient boosting, and at least one deep learning framework;
➢ Strong understanding of time-series modelling and statistical validation techniques;
➢ Experience with probabilistic forecasting approaches such as quantile regression, distributional models, or similar methods;
➢ Solid understanding of backtesting and model validation;
➢ SQL proficiency and experience with standard software engineering practices such as testing, packaging, and Git;
➢ Professional working proficiency in English.

Nice to Have:
➢ Previous experience within energy, electricity markets, renewables, battery storage, or energy trading is a strong advantage;
➢ Understanding of European electricity markets, including day-ahead/intraday markets, balancing, market coupling, cross-border flows, or ancillary services;
➢ Experience with weather-driven forecasting for solar or wind generation;
➢ MLOps experience, including model deployment, experiment tracking, model registries, CI/CD, retraining, and drift monitoring;
➢ Experience with cloud-based ML environments;
➢ Understanding of how forecasting models interact with mathematical optimization approaches such as MILP or stochastic optimization;
➢ Familiarity with BESS, ENTSO-E, JAO, or energy exchange APIs;
➢ Experience using AI-assisted development tools such as Claude Code, Cursor, or similar.

What They Offer:
➢ Opportunity to join a greenfield AI/ML project and influence the platform from its earliest stage;
➢ Direct exposure to real energy assets and live European energy markets;
➢ High level of technical ownership and freedom to experiment with different modelling approaches;
➢ Small, highly specialized team with a start-up mindset, backed by an established energy group;
➢ Hybrid working model;
➢ High-end technical equipment and access to modern AI development tools;
➢ Opportunity to work on technology with direct impact on energy efficiency, asset optimization, and the wider transition towards renewable energy.

If you enjoy building forecasting models that move beyond research and directly influence real-world decisions, this role offers the opportunity to work at the intersection of Data Science, Machine Learning, energy markets, and optimization while helping shape a new platform from scratch.