Data Scientist Forecasting
Pubblicato il 15-10-2026 - 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