Data Scientist

Data Scientist - Weather & Short-Term Power Job Description Data Scientist - Weather & Short-Term Power Posting Start Date: 10/1/26 Requisition ID: 67947

General information Brussel, Belgium, 1000 ENGIE GLOBAL MARKETS, BELGIAN BRANCH Trading / Portfolio Management Permanent Full - Time

Data Scientist - Weather & Short-Term Power (HL 14)

Location: Brussels

About ENGIE and Supply & Energy Management:

ENGIE, a global leader in low-carbon energy and services, relies on its Global Business Unit Supply & Energy Management (GBU S&EM) to provide reliable, sustainable, and affordable energy to all its customers. This strategic unit optimizes the Group’s and clients’ production assets and designs tailored energy solutions for our 200,000 professional clients and 15 million consumers.

The Global Business Unit Supply & Energy Management leverages ENGIE’s assets to deliver secure and sustainable energy to its B2B and B2C customers. It uses its expertise in energy management to provide decarbonized electricity 24/7.

Joining Supply & Energy Management means becoming part of a team of over 10,000 passionate experts spread across 20 countries, all united by a shared mission: shaping a greener and more efficient energy future. Together, we push the boundaries of innovation to deliver decarbonized energy 24/7. Join us and be part of those shaping the energy of tomorrow

Context

The Expertise Center Market Analysis and the Business Platform Power Trading, Structuring & Origination (PTSO) are looking for a Data Scientist - Weather & Short-Term Power to join the Short-Term Power Market Analysis (STP) team in Brussels. The position sits on the trading floor, embedded in an extended team of market analysts, meteorologists, hydrologists and data scientists.

The STP team covers short-term power markets - week-ahead, day-ahead, intraday, ancillary and imbalance - in support of trading and portfolio management activities in Central Western Europe (CWE). Weather has become the dominant driver of these markets: renewable generation, demand and prices are increasingly shaped by it, and extracting value from weather information is one of the team’s key priorities.

This is not a conventional power analyst position. We are looking for a data scientist with strong weather expertise, or a quantitative meteorologist, to act as a bridge between two teams: as a member of the STP team, the successful candidate will also be integrated in the Meteo & Climate team, strengthening the collaboration between them. Above all, the candidate will work in close daily contact with our internal clients: the short-term power trading and asset optimization desks.

Your Mission

As Data Scientist - Weather & Short-Term Power, your mission is to turn weather data into market value: translating weather forecasts - and their uncertainty - into actionable signals, forecasts and strategies for the short-term power trading and asset optimization desks.

Your main activities:

Develop, industrialize and maintain weather-driven forecast products and trading signals for day-ahead, intraday and imbalance markets, owning the full model lifecycle from research to production.

Exploit deterministic and ensemble weather forecasts (post-processing, calibration, skill evaluation) to extract predictive value for renewable generation, demand and prices in CWE.

Work daily with the trading desks: understand their needs, deliver weather intelligence in actionable form, and communicate forecast confidence and risks clearly and on time.

Act as the bridge between the STP and Meteo & Climate teams: co-develop tools and data pipelines, spread weather best practices within STP, and bring power market awareness to the weather team.

Monitor upcoming weather and alert traders and analysts on market-moving weather events and forecast revisions.

Contribute to the team’s roadmap, dashboards and digital platforms, staying ahead of advances in weather forecasting, data science and AI.

What we are looking for

Hard skills

In-depth knowledge of Numerical Weather Prediction models and weather data, including ensemble forecasting and reanalysis datasets.

Strong Python and data science skills: machine learning applied to time series, statistical post-processing, uncertainty quantification, and handling of large meteorological datasets.

Experience building, deploying and maintaining models in production; familiarity with cloud-based technologies (AWS, GCP or Azure) is a plus.

Knowledge of (short-term) power markets is a plus - a strong appetite to learn them is a must.

Soft skills

Clear and effective communication, written and verbal: able to convey complex weather and model topics to traders and non-specialists.

Strong team spirit and collaborative mi