Quantitative Analyst Sr

As our Senior Quantitative Analyst
, you will bring your data science expertise to the forefront of the energy industry—one of the most dynamic and rapidly evolving sectors. In this role, you’ll lead the development of advanced models to forecast electricity load and generate actionable insights from complex datasets. Your work will directly support smarter decision-making across pricing, risk, and energy management functions. You will build scalable, enterprise-grade tools and collaborate closely with cross‑functional teams in Pricing, Portfolio Management, and Digital.

With direct exposure to senior leadership, you’ll help shape data‑driven strategies that drive ENGIE’s continued success in competitive power markets.

This position sits in Houston, TX reporting to Quantitative Analytics Manager

• Take the lead in developing advanced forecasting models for electric load, uncovering actionable insights from complex datasets, and creating scalable, production‑ready tools for critical business decisions
• Collaborate with teams across Pricing, Portfolio Management, and Digital, engaging leadership to deliver impactful data‑driven strategies
• Execute daily “Pre‑Deal” operations, providing accurate and timely forecast support, and ensuring the reliability of forecasting platforms
• Partner with Power Portfolio Management, Pricing & Structuring, and the Costing t eam to analyze historical market trends, forward pricing, and market f undamentals, offering key insights into financial forecast variances
• Develop effective, sca lable code Python, Docker, SQL to optimize forecasting models and business tools
• Create and maintain robust Cloud data pipelines Azure Data Factory, AWS to ensure seamless data processing practices in Git repository management and requirements gathering, translating functional needs into technical Champion best solutions
• Utilize advanced statistical and predictive modeling techniques Machine Learning, Bayesian Statistics) to develop and refine decision‑support systems
• Res earch complex business problems such as load reconciliation, portfolio stress tests, or budget tracking, designing actionable, analytics‑driven solutions
• Introduce the latest data science trends, train others, and propose innovative solution s for end‑users to tackle challenges like load analysis, risk analytics, and pricing optimization
• Collaborate with third‑party vendors, developers, and consultants to enhance business processes A lign with ENGIE North America policies and procedures as a trusted team member
• Join a collaborative environ ment at the intersection of energy and advanced analytics, driving innovation and meaningful change
• Operate as a team member with all ENGIE North America NA staff employees

• You hold a Bachelor’s degree in a quantitative discipline such as Economics, Mathematics, Statistics, Computer Science, Physics, or a related STEM field. In lieu of a degree, we will accept a combination of seven (7) years of relevant professional experience where you have demonstrated applied knowledge in data analysis, statistical modeling, technical problem‑solving, and the use of analytical tools to support business decision‑making or operational improvements
• You have a minimum of five (5) years of professional experience, including at least two (2) years in analytical or technical roles
• You are a self‑starter who thrives in flexible, independent work environments and can manage complex technical tasks without close supervision
• You have strong programming expertise, proficient in multiple languages including Python, R, and SQL, and skilled in developing REST APIs and optimizing workflows
• You are knowledgeable in advanced statistical and predictive modeling, including machine learning, Bayesian statistics, decision trees, clustering, and bias detection techniques
• You have hands‑on experience with data engineering and ETL processes, as well as data visualization tools like Microsoft Power BI (DAX) and Microsoft Visio
• You are familiar with cloud infrastructure and Dev Ops environments, with experience using platforms such as MS Azure, AWS, and tools like Git Hub and Azure Dev Ops
• You have a strong understanding…