Senior Data Scientist - Flex Trading Strategy Development (f/m/d)

Senior Data Scientist - Flex Trading Strategy Development (f/m/d)

E.ON Energy Markets GmbH | Unbefristet | Vollzeit; Teilzeit

E.ON Energy Markets GmbH is a subsidiary of the E.ON Group based in Essen. Our main task is to coordinate access to the trading markets for our regional business units, to bundle the associated opportunities and risks and to provide innovative services. Our core competences include portfolio strategies, risk management and data processing. With a presence in various European countries, we are shaping the future of energy.

Diversity counts at E.ON. We welcome all people and believe that differences make us stronger. Become part of our inclusive and diverse corporate culture!

Seize the opportunity to become part of our E.ON Energy Markets GmbH team in Essen at the earliest possible date and apply online now as Senior Data Scientist - Flex Trading Strategy Development (f/m/d). We are seeking a motivated and curious Working Student to join our dynamic team. This is an excellent opportunity for a student passionate about software development and operations to gain hands-on experience with modern technologies such as Kubernetes and testing frameworks.

Key Responsibilities

Take ownership of the development and optimisation of quantitative trading strategies for dispatching flexible assets across intraday, day-ahead, balancing, and ancillary service markets.

Build in collaboration with other teams predictive models for price forecasting, asset availability, imbalance signals, and market spread identification to improve bidding and scheduling decisions.

Own the trading strategy roadmap, identify, prioritise, and deliver new features and model improvements in iterative cycles aligned with business value.

Collaborate closely with traders to validate hypotheses, back-test strategies against real P&L, and incorporate trader intuition into model design.

Scale strategies across geographies and asset classes, adapting to local market rules, grid codes, and asset-specific technical constraints (e.g., degradation, ramp rates, state-of-charge).

Design and maintain robust data pipelines that feed real-time and historical market, weather, and asset data into modelling and decision engines.

Monitor live strategy performance, detect drift or anomalies, and implement rapid feedback loops for continuous improvement.

Communicate results clearly to both technical and non-technical stakeholders, translate complex model outputs into trading insights and strategic recommendations.

Stay current with developments, and state-of-the-art methods in ML/optimisation relevant to energy trading.

Your Profile

MSc or PhD in Data Science, Statistics, Mathematics, Physics, Computer Science, Operations Research, or a related quantitative field.

10+ years of professional experience applying data science or quantitative modelling in an energy trading, energy tech, or commodity trading environment.

Proven track record of developing and deploying IT/data-driven solutions that directly support trading decisions or automated dispatch using MLOps tooling and CI/CD for model deployment

Deep understanding of European electricity markets (EPEX, Nord Pool, or equivalent) including day-ahead, intraday continuous, and balancing mechanisms.

Excellent programming skills in Python (pandas, NumPy, scikit-learn, LightGBM/XGBoost, or similar); SQL and cloud-based data platforms.

Experience with reinforcement learning, Bayesian methods, or time-series deep learning (LSTMs, Transformers) in a trading context.