Data Science Forecaster Rotterdam • Eneco

As a Data Scientist in the Quant Forecasting Team (Forecast Product Development), you will play a pivotal role in researching and developing forecasting products that meet the needs of our stakeholders, e.g. intraday traders, day-ahead traders,.. Our forecasting products include proprietary power production forecasting models for wind and solar energy, as well as other tools designed to enhance forecast accuracy and provide deeper insights. Your primary focus will be on analyzing the impact of various weather sources on our portfolio, as well as researching, improving, and building new forecasting products.

You will be in constant contact with stakeholders, updating forecasting products based on portfolio demands, and improving products in terms of reliability, scalability, accuracy, and stakeholder insights. Collaboration with teams such as IT and Operations is essential. Our team aims to provide precise, reliable, and actionable insights that drive our trading strategies and decisions. We believe that by embracing data, analytics, business insights, and AI, we can transform the future of energy trading.

Finally, you will have a direct impact on the energy market and should have a pioneering mindset as a team player. We are searching for a team player who is critical but pragmatic and contributes to a psychologically safe environment. In this pioneering role, you will have ample opportunities to develop yourself both personally and technically.

As a Data Scientist in the Quant Forecasting Team, you will work on forecasting models and data products that power real-time energy trading decisions. Your key responsibilities:

• Research the impact of different weather sources (e.g. NWP models, AI-based nowcasting) on our renewable production portfolio
• Develop and continuously improve our short-term forecasting models for wind and solar energy
• Collaborate with intraday and day-ahead traders to adapt forecasting tools to real-world needs
• Build scalable, accurate, and resilient forecasting products in close collaboration with IT and Operations
• Deliver actionable insights that reduce P&L risk and improve trading performance
• You’ll work at the intersection of data science, meteorology, and energy trading – in a team that values innovation, autonomy, and collaboration.

We’re looking for a data-savvy forecaster who wants to make a real impact:
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• MSc or PhD degree in Data Science, Physics, Applied Mathematics, or related field
• 5 Years of experience with time series forecasting, ideally involving weather data
• Proficient in Python and relevant data science tools (e.g. pandas, scikit-learn, NumPy)
• Familiarity with tools like Databricks, Airflow, Snowflake, Docker, Azure, and CI/CD is a plus
• Communicative, curious, and eager to co-create with both business and tech colleagues
• A proactive and pragmatic team player who thrives in a fast-moving, high-impact environment
• • Knowledge and experience related (or similar) to software engineering or ML engineering is a plus.
  • Relevant concepts include: MLOps, CI/CD, `software` testing
  • Relevant technologies include: Databricks, Airflow, Snowflake, Docker, Azure Cloud
• Knowledge and experience of energy markets is a plus.

Working at Eneco means working at a sustainable company where we strive for a new world. A world that is smarter, better, cleaner, more enjoyable, and more liveable. We do this together with more than 3,000 colleagues, following ‘the new way of working’, in a beautiful modern building: Eneco World. Eneco World is easily accessible: just a two-minute walk from Rotterdam Alexander metro and train station.

TheQuant Forecasting Team (Forecast Product Development) is part of the Short Term Trade Desk  of Eneco Energy Trade (EET). With a diverse team of motivated and highly educated employees, we work towards an optimal market vision that supports Eneco’s sustainability goals. EET provides a dynamic and complex working environment that requires a lot of initiative and insight. We communicate quickly with each other in an informal, transparent, and collegial atmosphere.