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Position Purpose: The Energy Market Optimization Engineer reports to the Division Director with primary responsibilities of developing and deploying advanced optimization models and machine learning solutions for bid/offer strategies within ISO (Independent System Operator) energy markets. This role focuses on maximizing revenue across microgrids, battery energy storage systems (BESS), and renewable energy assets through data-driven market optimization. The position collaborates closely with energy operations teams to design, implement, and continuously improve algorithmic strategies informed by market data, price forecasting, and asset performance analytics.
Job Responsibility:
Design, develop, and implement models to optimize bid/offer strategies for asset participation in ISO energy markets (PJM, MISO, ISO-NE, etc.), in collaboration with energy operations teams
Build predictive models for energy price forecasting, load forecasting, and renewable generation forecasting to inform and improve bidding strategies
Develop optimization algorithms for battery storage dispatch, considering state-of-charge constraints, degradation costs, and market price signals
Collaborate with energy operations teams to develop offer strategies that maximize revenue while managing risk and operational constraints
Monitor model performance, conduct backtesting, and continuously improve algorithms based on market outcomes
Assist in developing data pipelines to ingest, process, and analyze large-scale market data, weather data, and asset performance data
Communicate insights and recommendations to stakeholders through visualizations, reports, and presentations
Requirements:
Bachelor's degree in Data Science, Computer Science, Statistics, Operations Research, Electrical Engineering, or related quantitative field
5+ years of experience applying machine learning and optimization techniques to real-world problems
Experience with optimization frameworks and mathematical programming
Some experience with ISO energy markets and understanding of market structures (preferred)
Experience with reinforcement learning applications in sequential decision-making problems (preferred)
Familiarity with energy market simulation and backtesting frameworks (preferred)
Understanding of power systems fundamentals and grid operations (preferred)
Solid understanding of machine learning algorithms including regression, time series forecasting, reinforcement learning, and ensemble methods
Strong analytical and problem-solving skills with attention to detail
Excellent communication skills and ability to explain complex technical concepts to non-technical stakeholders
Ability to work in a fast-paced business environment
Ability to work closely within a team environment
Good time management skills
Nice to have:
Some experience with ISO energy markets and understanding of market structures
Experience with reinforcement learning applications in sequential decision-making problems
Familiarity with energy market simulation and backtesting frameworks
Understanding of power systems fundamentals and grid operations