Description
About 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 (EC) Quantitative Research and Modeling (QRM) within S&EM is a team of around 100 quantitative analysts and data scientists. Its mission is to provide advanced quantitative expertise to the various Business Platforms (BP) of S&EM.
The data scientist sought here will join the “Short Term Trading” team of QRM (around 10 people) and will be fully dedicated to the BP Power Trading & Commercial (PT&C), with a focus on activities related to the short term power markets in Northwest Europe.
Your Mission
The VIE candidate will work on topics linked to day-ahead, intraday, and imbalance power markets.
They will handle large datasets and use statistical tools, machine learning, and advanced quantitative models to deliver analyses and tools that have a concrete business impact, including:
• predicting relevant power market signals (volumes, prices),
• optimizing assets such as Battery Energy Storage Systems (BESS),
• developing trading strategies and algorithms.
• Key responsibilities include:
• Contributing to the continuous development and improvement of optimization and trading models/tools.
• Leveraging large data volumes to provide insights to trading desks.
• Collaborating with traders to understand needs and propose adapted solutions.
• Exchanging with analysts to benefit from peer expertise.
• Coordinating with IT teams on topics related to architecture, deployment, and industrialization.