Senior Data Scientist – Optimization; Energy Systems

Senior Data Scientist – Optimization (Energy Systems)

We are seeking a Senior Data Scientist with deep experience in MILP-based optimization to build, scale, and improve decision-optimization and forecasting systems for complex energy use cases. This role is embedded within the Product team and focuses on extending a production optimization engine, improving solution accuracy, and enabling new programs and constraints across energy systems and distributed energy resources (DERs). This is a hands‑on, senior role for candidates with a strong operations research foundation, experience using Python and Pyomo, and the ability to translate business objectives into scalable optimization solutions.

• Design, prototype, and implement enhancements to a MILP-based optimization engine
• Extend core data models and optimization formulations to support new use cases, programs, and constraints
• Integrate and scale optimization logic with solvers and production systems
• Benchmark optimization performance across program stacks, load profiles, locations, and other key variables
• Build robust test coverage for new and existing optimization logic
• Monitor optimization accuracy at the customer‑site level and proactively identify anomalies
• Diagnose root causes of optimization accuracy issues and propose product improvements
• Collaborate with product, engineering, and business stakeholders to align optimization and forecasting with economic objectives
• Analyze market price behavior and propose strategies to improve asset utilization
• Quantify the incremental value of optimization changes to support product prioritization
• Identify new data science‑led opportunities and incorporate internal and external data sources
• Contribute to building and scaling a data science and optimization practice over time

• Bachelor’s or Master’s degree in Computer Science, Operations Research, Mathematics, Statistics, Engineering, Physics, or a related field
• 7+ years of experience in data science, optimization, or a related quantitative field
• 2–5+ years of hands‑on experience with MILP-based optimization (professional experience preferred; advanced academic experience acceptable)
• Strong proficiency in Python and Pyomo, with experience implementing optimization models in production
• Experience with mixed‑integer optimization techniques and solver integration
• Knowledge of time‑series forecasting and machine learning methods (e.g., ARIMA, LSTM, probabilistic models)
• Experience with model predictive control or sequential decision‑making systems
• Experience working in Agile, cross‑functional product development environments
• Ability to clearly communicate technical concepts and manage stakeholder expectations
• Authorization to work in the United States without current or future visa sponsorship

• Experience with electricity markets, utility tariffs, and interval data
• Familiarity with DER assets such as batteries, solar, and backup generation
• Experience forecasting energy prices, system peaks, or demand response events
• Advanced experience with Azure, Postgres, or similar cloud/data platforms
• Software development experience in Python and/or .NET
• Experience building or leading a data science or optimization practice

• Work on real‑world, large‑scale optimization problems with direct business impact
• Collaborate with experienced product and engineering teams in a growing organization
• Gain deep exposure to energy systems, DER optimization, and electricity markets
• Competitive compensation and comprehensive benefits including medical, dental, vision, 401(k), vacation, and up to $10,000/year in tuition reimbursement