Lead Data Scientist Stochastic Modeling

About the Role

Grade Level (for internal use):

12

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:

Basic Required Qualifications:

• Advanced degree (MSc or PhD preferred) in a highly quantitative discipline such as Statistics, Mathematics, Computer Science, Physics, Engineering, or Operations Research, with strong experience in stochastic modeling, optimization, or statistical inference.
• Deep expertise in probabilistic modeling, uncertainty quantification, Monte Carlo methods, and modern machine learning techniques, with the ability to apply them to complex real-world problems.
• Strong programming skills in Python (and/or R), including experience with scientific computing libraries that are similar to NumPy, pandas, SciPy, scikit-learn and modern ML frameworks that are similar to PyTorch or TensorFlow.
• Experience building scalable, production-oriented solutions using cloud platforms that are similar to AWS, GCP, or Azure, containerization tools that are similar to Docker, Kubernetes, and collaborative development workflows that are similar to Git, CI/CD.

Key Soft Skills

• Strong problem-solving mindset with the ability to quickly understand new domains and translate ambiguity into structured, actionable solutions.
• Clear and effective communicator, capable of explaining complex technical concepts to both technical and non-technical stakeholders.
• High level of ownership and accountability, with the ability to move independently from concept through validation and deployment.
• Collaborative team player who contributes to a culture of rigor, curiosity, continuous learning, and mentorship.

Additional Preferred Qualifications:

• Experience with quantum computing applications, including quantum machine learning or quantum optimization methodologies.
• Familiarity with generative AI, synthetic data generation, and advanced simulation techniques for complex system modeling.
• Domain knowledge in energy markets, commodity analytics, or related industrial sectors.
• Demonstrated record of research impact, such as publications in peer-reviewed journals or presentations at leading academic or industry conferences.
• Experience working with large-scale data ecosystems that are similar to Spark, Hadoop and strong understanding of data governance, privacy, and security best practices

What’s In It For You?

Our Mission:

Advancing Essential Intelligence.

Our People:

We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values:

Integrity, Discovery, Partnership

Throughout our history, the