Data Scientist, Battery Optimization

Develop and maintain advanced mathematical models for asset optimization.

• Drive automation and scalability.
• Collaborate closely with teams across Trading, Forecasting, Tech, and Operations to deliver integrated, high-impact solutions.
• Optimize energy asset dispatch through mathematical modelling (Gurobi).
• Design and implement monitoring frameworks for asset performance based on real-time/realized asset data.
• Ensure operational stability together with traders, Tech, product managers, and dispatchers.

Quantitative MSc or equivalent experience in Computer Science, Mathematics, Statistics, Econometrics, Physics, or a related quantitative field.

• Around 5 years of experience in data science roles.
• Prior experience in the energy sector or trading is considered a plus.
• Experience with building and deploying scalable trading and/or optimization algorithms in the cloud.
• Strong background in Python development, including writing modular and clean code, implementing unit tests, and proper monitoring.
• Familiarity with SQL databases, Databricks, and streaming data.
• Understanding of business problems and ability to translate them into robust data-driven solutions.
• Familiarity with Azure Cloud, Gurobi, Kubernetes, Databricks, Airflow, Snowflake.
• Strong command of English (Dutch is a plus).

At Eneco, we are driving the energy transition by optimizing batteries and diverse energy assets. Our international trading division, Eneco Trading, is dedicated to becoming a leading player in the European energy market. We focus on delivering flexibility and grid stability through sustainable energy. Located in Rotterdam, Eneco World is our modern headquarters, and we embrace a hybrid work model to support a work-life balance. Our diverse team consists of around 18 professionals, collaborating effectively to implement sustainable change. We offer competitive salaries, personal growth opportunities, and a commitment to climate neutrality by 2035.