Short Term Forecasting Data Scientist
Role details
Job location
Tech stack
Job description
The world around us is changing fast. Eneco is a frontrunner in the energy transition by integrating new sustainable energy sources and innovative ways of storing and managing energy. At the same time, customer needs are evolving rapidly, and so must we.
Within Eneco Trading Community, our international trading division, we aim to be a leading player in the European energy market, delivering flexibility and grid stability through sustainable energy. 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! You will work in a company that is large enough to get things done and diverse in people and technology, yet agile and innovative enough to move fast. At Eneco, anyone with a sharp mind and a positive attitude can make a difference.
The Forecasting Analysis & Execution team within the Short-Term Desk develops continuously updated forecasts for energy demand and renewable energy generation. These forecasts directly support short-term energy trading decisions. As a Forecasting Data Scientist, you help optimize Eneco's trading results while contributing to a more sustainable energy system. In this way, your work supports Eneco's ambition to make the energy transition both impactful and economically attractive by 2035.
Your contribution focuses on minimizing (imbalance) costs related to wind and solar production and customer demand. You work in a fast feedback environment where learning, reflection, and continuous improvement are part of everyday work, both individually and as a team.
You will collaborate closely with the Forecast Product Development team to design, improve, and operationalize forecasting products, such as in-house wind and solar power models. You also work together with traders, providing clear insights and decision support, and develop monitoring and reporting tools that increase transparency and understanding of the trading portfolio.
-
Collaborate with our Forecast Product Development team to develop, improve and validate forecasting models for wind/solar production and power/gas/heat consumption;
-
Develop monitoring and reporting software-products to support the trade departments;
-
Work within a DevOps framework and promote this methodology, including Azure DevOps (CI/CD), Databricks (Python & SQL) to the team;
-
Validating and analyzing data (e.g., identifying irregularities and outliers in forecasting model outputs).
-
Quantitative MSc in a relevant field (e.g. Data Science, Mathematics, Physics, Econometrics or similar);
-
4+ years of professional experience in data science;Strong programming skills in Python and SQL;
-
Experience working with modern data and ML tooling such as Git, Databricks, Airflow, Snowflake or Azure Cloud;
-
Familiarity with software/ML engineering practices such as DevOps, CI/CD, software testing and MLOps;
-
Analytical, critical and hands-on mindset with strong attention to detail and the ability to build robust solutions;
-
Experience or strong interest in energy markets or trading is a plus.
You will join a relatively young team where collaboration and open communication are highly valued. Everyone in the team combines operational responsibilities with long term strategic development projects, ensuring that technical improvements are directly connected to real-world decision-making.
Operational tasks include analyzing monitoring results and supporting day traders by answering questions about positions and forecasts, and handling incidents when systems, data flows, or forecasts are not behaving as expected. Staying calm and stress-resilient is essential. These activities provide valuable context and help identify opportunities to further improve our tools and models.
During your first months, you will be supported in building a strong understanding of the energy market, Eneco's role within it, and our IT landscape. The role offers a healthy balance between hands-on work and development, with room to experiment, propose ideas, and see the impact of your work quickly.
- Build and improve forecasting models used in live energy trading
- Work with Python, Databricks and modern DevOps/MLOps tooling
- Combine data science with real-world impact in the energy transition
Requirements
- Quantitative MSc in a relevant field (e.g. Data Science, Mathematics, Physics, Econometrics or similar);
- 4+ years of professional experience in data science;Strong programming skills in Python and SQL;
- Experience working with modern data and ML tooling such as Git, Databricks, Airflow, Snowflake or Azure Cloud;
- Familiarity with software/ML engineering practices such as DevOps, CI/CD, software testing and MLOps;
- Analytical, critical and hands-on mindset with strong attention to detail and the ability to build robust solutions;
- Experience or strong interest in energy markets or trading is a plus.