Develop optimization models for marketing flexibility from battery storage systems, industrial loads and power‑to‑heat plants on short‑term electricity markets and in reserve/balancing markets
Own responsibility for our commercialization performance in the energy markets
Implementation, deployment and monitoring of robust data‑science solutions in a production real‑time system
Research & development of machine learning models, e.g., for energy‑related applications such as price and consumption forecasting or energy trading
Establish measurable performance KPIs and use them for continuous product improvements
Close collaboration with Tech, Business Development and Product Management

Degree in Electrical Engineering, Computer Science, Mathematics, Statistics, Physics, or a comparable qualification
Practical experience with machine learning, time series forecasting and/or optimization algorithms, ideally in the energy or financial sector
Strong software and systems knowledge, e.g., Python, testing, code quality, monitoring and visualization
Preferably advanced knowledge of the energy industry
Experience designing, querying and optimizing relational databases and efficiently handling large datasets
Analytical and conceptual thinking for solving complex problems
Fluent in German and English, both spoken and written

Innovative, dynamic and technologically challenging field of work supporting the energy transition
Responsibility with broad scope for design and decision‑making and strong potential for personal development
Agile team with flat hierarchies and short decision‑making paths
Collegial and open working atmosphere
Modern, centrally located and well‑equipped offices with excellent public transport connections at both locations
Hybrid or mobile working: flexible mix of presence in our offices in Munich or Berlin and remote work

Data Scientist, Quant - Flexibility Marketing

Key skills