LeadDataScientistStochasticModeling

# **About the Role:** **Grade Level (for internal use):** 12 **S &P Global Commodity Insights ** **The role: Lead Data Scientist Stochastic Modeling** **The Team:** The team is a highly analytical and solution-oriented group focused on solving complex, cross-disciplinary problems using machine learning, physics-based modeling, optimization, and data/UI engineering. We translate ambiguity into structured, practical solutions and move efficiently from concept through validated prototype to production deployment. We value intellectual curiosity, rigorous thinking, clear communication, rapid domain learning, and strong ownership throughout the project lifecycle. **Responsibilities and Impact:** * Lead the design, development, and validation of stochastic, physics-based, and optimization models to solve complex real-world problems in the energy sector, with strong focus on uncertainty quantification, risk analysis, and scenario simulation. * Translate ambiguous business challenges into structured analytical frameworks, rapidly prototype solutions (machine learning models, optimization engines, interactive dashboards), and deliver validated, production-ready tools. * Conduct applied research to advance modeling methodologies, integrating advanced statistical techniques (e.g., Bayesian inference, Monte Carlo simulation, Markov and Gaussian processes) with modern machine learning frameworks. * Collaborate closely with software engineers, domain experts, and deployment teams to ensure scalable architecture, reproducible workflows, and seamless transition from research to production. * Leverage cloud platforms (AWS, GCP, Azure), data engineering best practices, and emerging technologies including generative AI to build robust, efficient, and maintainable solutions. * Communicate complex technical insights clearly to diverse stakeholders and mentor junior team members, fostering a culture of rigor, curiosity, ownership, and continuous learning. ** _What We’re Looking For:_** *