Data Scientist - Hedging & Risk Management (Renewables

ENGIE North America is seeking a highly analytical and technically skilled Data Scientist to join the Hedging & Risk Management team supporting our renewable energy portfolio. In this role, you will apply advanced analytics, data science, and technology to transform complex markets, portfolio, and risk data into actionable insights that strengthen decision-making and support the financial performance of our renewable assets.

You will combine expertise in data science, software development, financial modeling, and cloud-based analytics platforms to develop scalable analytical tools, automate processes, enhance risk and exposure mapping, and improve the quality and speed of commercial insights. Working closely with Hedging & Risk Management and cross-functional partners, you will play a key role in advancing the team's digital capabilities and enabling more informed, data-driven risk management decisions.

• Design and implement scalable digital solutions that replace manual processes, improve operational efficiency, and strengthen decision-making across Hedging & Risk Management
• Maintain and enhance digital platforms supporting renewable energy and battery energy storage system (BESS) activities
• Identify and implement opportunities to automate data collection, validation, workflow, and reporting processes
• Drive continuous improvement initiatives across risk management, hedging, and commercial operations

• Develop predictive models, optimization algorithms, and analytical frameworks that support portfolio, commercial, and risk management objectives
• Apply statistical modeling, machine learning, and quantitative techniques to evaluate market, operational, and portfolio performance
• Build scalable analytical tools for forecasting, scenario analysis, sensitivity analysis, and performance benchmarking
• Translate complex data and model outputs into actionable insights for business stakeholders
• Design methodologies to identify, quantify, monitor, and visualize market, operational, and financial risk exposures across renewable and battery storage portfolios
• Develop risk metrics, analytical frameworks, and dashboards that improve visibility into portfolio exposures and performance
• Perform stress testing and sensitivity analysis to evaluate portfolio response to changing market and operational conditions
• Enhance risk reporting capabilities through improved analytics, automation, and data visualization
• Partner with Group Risk, short-term trading, and commercial teams to evaluate hedging strategies, market exposures, and portfolio performance
• Deliver quantitative analysis that supports price risk management, portfolio optimization, and strategic decision-making
• Develop tools and methodologies to assess hedge effectiveness, market exposure, and the financial impacts of alternative hedging strategies
• Provide analytical support for evolving renewable and BESS risk management strategies

• Automate recurring financial, portfolio, and risk reporting using modern data platforms and business intelligence tools
• Develop dashboards and self-service analytics solutions using Power BI and other visualization platforms
• Transform complex datasets into intuitive visualizations that enable stakeholders to quickly understand trends, exposures, and performance
• Maintain data quality, integrity, governance, and traceability across analytical models, tools, and reporting solutions

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related quantitative discipline; a master’s degree in a quantitative discipline may complement relevant experience but is not required
• Minimum seven (7) years of relevant experience in data science, advanced analytics, quantitative or predictive modeling, market risk analysis, hedging, or related analytical roles
• Advanced proficiency in Python with experience developing reliable, scalable analytical solutions
• Proficiency in SQL and experience working with relational databases,…