Data Scientist

Requisition ID: 9186- Location: Courbevoie, FR, 92400**About US (GEMS)**: ENGIE Global Energy Management & Sales (GEMS) provides energy supply solutions and risk management services to support its clients through their decarbonization journey, while optimizing ENGIE’s assets and contributing to value creation. ENGIE is a global reference in low-carbon energy and services with a leading energy management business, piloted by its entity "Global Energy Management & Sales" who built its savoir-faire managing the Group’s large and diverse asset portfolio over 20+ years. 3,300 employees around the world develop our solutions, through +20 international business platforms. We cover the full energy mix: renewable and thermal power, natural gas & LNG, biomass, environmental products. Our experts provide tailor made solutions based on a wide range of savoir-faire in energy management with a strong focus on decarbonation and decentralization. Our +120,00 clients span the entire value chain: producers, asset developers, financial players, utilities, distributors and industrials. Our global reach and strong local presence enable us to offer these diverse clients tailor-made services and respond to rapid changes in mature or emerging markets alike. Our 4 expertises: - Asset management - Energy transition services - Energy supply & global commodities - Risk management & market access At GEMS we encourage breakthrough results, team spirit, curiosity and innovation while preserving the right work/life balance for you. **Context**: The position belongs to the Quantitative Data Analysts team (GEMS/BP Downstream) specifically dedicated to assist the management of risks for the commercial B2C and B2B BUs in France which supplies energy to French customers. **The main missions associated with the position are**: - Based on data collection, to build models, tools, processes and data representations, that are used to manage the commodity risks linked to the dynamics of a Supply portfolio, - The purpose of this work is to operate and optimize costing, forecasting, sourcing and hedging strategies, within a defined mandate, - The quantitative analyst / data scientist will do the design, but also the development and ensure the delivery of these models and tools. Beyond that, he will also provide scientific expertise for bespoke analysis, related to data or models, - As a member of the quantitative analysts community of the Business Platform Downstream, the quantitative analyst/data scientist can also contribute to transversal projects impacting the activity of other commercial BUs. **Role**: The daily responsibilities of the new role will include: - Contribute to the development of the tools, models, process and portfolio/data representation used for: - Representation of all commodity exposures and associated risks (evolution of the commercial position, climatic impact on short term consumption forecasts, churn,...), - New commercial offers, - Customer behavior analysis. - Ensure the run of models and derived operations, - Provide BUs B2C and B2B France with a deep knowledge of its commodity sales portfolios (Natural Gas, Power and Certificates) and optimally structure the portfolio representation in order to monitor and clearly report on operational performance and risk drivers, - Use a vast range of data to ensure correct representation, - Promote good practice, especially around data and code, - Ensure code quality by following general rules and standards, - Interact with other quantitative analysts/data scientists from the BP Downstream, to exchange about models, data, business or technical topics beyond the team. **Hard skills**: - **Must have**: - Strong scientific background: mathematics (probability/statistics), data science, machine learning, ideally with good command of time series forecasting, - Strong skills in software (ideally Python) programming and related tools (versioning, etc.), - Willingness to embrace data handling and operational analytics, - Practical thinking, hands-on approach. - **Good to have**: - Knowledge of modern data science platforms and engines such as Databricks and Spark is a plus, - Interest for the Energy markets and Energy-transition topics. **Soft skills**: - **Must have**: - Ability to take initiatives and challenge the “as-is” situation, - Ability to explain and convey messages about complex issues to non-experts in a simple and pedagogic way, - Practical thinking, Entrepreneurship, - Team-player, Transparent, Favor collaboration and working together. - **Good to have**: - Planning - Conceptual thinking **Education and professional background**: - University degree in Engineering, Computer Science, Statistics, Mathematics or Physics - At least 2-5 years of experience in the development of modelling tools, ideally with a good knowledge of electricity & gas markets **Languages**: - Fluent in English **Travels**: Occasional travels (mostly to Brussels, working plac