Data Scientist - Flex Optimization

The energy transition is in full swing and Eneco is leading the way. Our goal? Sustainable energy for everyone. This applies to our own business activities, but also to the energy we supply to our customers. For example, we develop wind and solar farms ourselves, and we help customers take sustainable steps every day with smart products and good advice. At the core of this mission lies our commitment to using advanced data science to operate and optimize our complex and diverse asset portfolio. Do you want to help us shape a sustainable future? Then we're looking for you!

As a Data Scientist in the Flex Optimization team, you’ll work on data driven solutions that maximize the value of Eneco’s steerable asset portfolio - including gas-fired power plants, renewable assets, batteries, industrial e-boilers, and behind the meter assets amongst others - by optimizing their flexibility across short-term power and ancillary markets.

• Your work will impact Eneco’s trade result and contributes to a smarter, cleaner energy system.
• You will build optimization strategies, bidding algorithms and machine learning models that operate in fast-moving, real-time energy markets.
• You will work side by side with other data scientists and traders to see where data science can add the most value.
• You will be working with large and growing datasets, so a continuous effort to improve forecasting, modelling, and decision support tooling is essential to stay ahead. Apart from developing these models you will also play a pivotal role to productionize them in a robust and reliable manner.

We aim to have a fast feedback loop of deploying, learning and adjusting, meaning that there is a strong focus on ownership and scalable automation of processes. Deploying your model makes real world impact – often the same day!

• Developing and maintaining advanced analytical models for cross-market optimization and bidding strategies. Using machine learning and (non)linear optimization methodologies.
• Designing and implementing new flexibility value propositions, from grid-scale batteries to behind the meter solutions, that enhance customer value and system flexibility.
• Driving automation and scalability, identifying where manual processes can be streamlined and operationalized.
• Collaborating closely with teams across Trading, Forecasting, IT, and Operations to deliver integrated, high-impact solutions.

• You have a quantitative MSc or equivalent experience in Computer Science, Mathematics, Statistics, Econometrics or a related quantitative field.
• You bring around 5 years of experience in data science roles, with prior experience in (energy) trading being considered a plus.
• You have experience with building and deploying scalable forecasting, trading and/or optimization algorithms in the cloud.
• Strong background in Python development: you know how to write modular and clean code, implement unit tests and proper monitoring.
• You understand underlying business problems, can distinguish between main and secondary issues and are able to translate these into robust data driven solutions.
• You have experience with SQL databases, Databricks and streaming data.
• Proactively initiating improvements and your drive to get things done is key.
• You are familiar with - parts of - our tech stack: Azure Cloud, Kubernetes, Databricks, Airflow, Snowflake.

You will work within the Flex Optimization team for the Trade Community - Eneco's international trading division - right next to Rotterdam-Alexander station. A complex, dynamic environment where moving markets, ever-changing positions, new technologies, and the law of inhibiting head start create a challenging field of tension which requires a lot of initiative and insight. We interact quickly with each other in an informal, transparent and collegial atmosphere. In a rapidly changing energy landscape, you and your team will shape the energy transition. A tough job, with challenging but achievable targets.