Senior Quantitative Statistician

What You Can Expect As a Senior Quantitative Statistician at ENGIE Energy Marketing North America (EEMNA), you will play a critical role in advancing probabilistic forecasting for our energy platforms. Working closely with the Head of Market Analytics and collaborating with a team of data scientists, software engineers, and business stakeholders, you will design and implement innovative statistical models that capture uncertainty across weather, load, grid conditions, and other critical parameters. Your work will directly impact our ability to simulate and forecast complex grid behavior, helping shape advanced AI-driven tools used for real-time decision-making and long-term planning. This role is ideal for someone with deep expertise in climate or weather modeling, statistical mechanics, and probabilistic methods, who thrives in fast-paced, high-impact environments. Reporting to the Head of Market Analytics, your roles and responsibilities include: Analyzing, quantifying, and modeling correlated uncertainty across hundreds of variables - including weather, load, grid outages, and other grid parameters Develop methodologies to create future grid and weather scenarios across timescales ranging from hours to years which preserves variable relationships and correlations Use Monte Carlo simulations and other statistical techniques to build probabilistic forecasts across varying time horizons Collaborate with the data science team to integrate scenario generation into physics-based and AI grid models Evaluation, quantifying, and monitoring performance of scenario generation in terms of coverage, accuracy, and variability Analyze variable sensitivities and their influence on forecast outputs Interface with business stakeholders to understand critical use cases and define modeling parameters accordingly What You'll Bring Minimum of a Master's degree in Statistics, Climate Science, Applied Mathematics, or a related quantitative field A minimum of five (5) years of experience building probabilistic forecasts Experience working with weather or climate forecasting in applied or research environments Proficiency in linear algebra techniques such as eigenvalue decomposition, principal component analysis (PCA), and Cholesky decomposition Understanding of correlated uncertainty quantification and statistical modeling methods Experience with Monte Carlo simulations and scenario analysis Proficiency in a programming language such as Python (or similar) for statistical modeling and simulation Ability to clearly communicate technical concepts to non-technical stakeholders and document complex methodologies Collaborative, team-oriented mindset with a proactive and detail-focused work style Additional Details This role is eligible for our hybrid work policy in our Houston, TX; Chicago, IL; and Broomfield, CO offices. For highly qualified candidates based in Pittsburgh, PA, a fully remote arrangement may be considered, provided the individual can travel to the Houston office for at least one week each month Must be available to travel domestically up to 15% of the time and with the need for some overnight trips Must be willing and able to comply with all ENGIE ethics and safety policies Compensation Salary Range:

$131,000 - $200,790 USD annually ENGIE complies with all federal, state, and local minimum wage laws. Actual salary offered may vary depending on geography, experience, education, internal pay alignment, or other bona fide factors. In addition to base pay, this position is eligible for a competitive bonus / incentive plan. At ENGIE, we take your well-being seriously. Our comprehensive benefits package includes options for medical, dental, vision, life insurance, employer-paid short-term and long-term disability insurance, ESPP, generous paid time off including wellness days, holidays and leave programs. ENGIE is proud to be an equal opportunity workplace, and we are firmly committed to creating an inclusive workplace for all employees. We are committed to providing employees with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

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