Data Scientist Forecasting
Pubblicato il 10-10-2026 - ENGIE in Pavia
Overview As a Forecasting Data Scientist in ENGIE’s Supply & Energy Management, you will develop and refine forecasting tools for the energy supply business. You will work with cross-functional teams to ensure accurate, timely forecasts that inform costing, sourcing, and hedging. You’ll implement state-of-the-art models aligned with global standards, while promoting best practices and knowledge sharing across geographies. Your work supports decarbonized, reliable energy solutions for B2B and B2C customers.
Responsabilità
- Design, implement, and improve forecasting tools, models, and processes for the energy supply business
- Develop forecasting components for new commercial offers aligned with market dynamics
- Analyze customer behavior to improve forecasting accuracy and relevance
- Utilize diverse internal and external data sources for robust portfolio and consumption representation
- Advocate for data handling and coding best practices across the team and broader community
- Ensure high-quality, maintainable code following development standards
- Collaborate with quantitative analysts and data scientists across teams to share models, data, and insights
Requisiti fondamentali
- Master’s degree or PhD in applied mathematics, engineering, data science, physics, economics, or related quantitative field
- Strong analytical mindset with ability to translate data into actionable insights
- Clear and effective communication skills for technical and non-technical stakeholders
- Collaborative and inclusive team player with an innovation-driven mindset
- 2+ years of experience in forecasting, data science, or quantitative analysis, preferably in energy
- Proficient programming in Python and R with version control knowledge (Git)
- Knowledge of Databricks and Spark is a strong asset
- Experience with cloud-based analytics environments and forecasting/portfolio management tools
- Fluency in English
- clear communication
- collaboration
- creativity
- Python
- R
- Databricks