Quant Researcher, Power Dispatch Modeling

Role/Responsibilities Building, running, and maintaining power dispatch model for ERCOT and other major US ISOs Driving the model’s inputs and architecture to efficiently simulate power grid conditions and marginal pricing Continuously testing and improving the model, ensuring it accurately replicates historical conditions and effectively analyzes forward scenarios Communicating the model’s results and limitations to the wider investment team Formulate and build a power dispatch model using Python and a commercial solver Collaborate with the PM to optimize model inputs and architecture Ensure the model replicates grid operations from historical conditions Suggest model improvements to decrease forecast error and improve scenario handling Regularly run the model and maintain up-to-date outputs in an internal database Communicate results and limitations to the wider investment team, including publishing results to team dashboards Requirements Master or PhD in operations research, electrical engineering, applied mathematics, or a related quantitative field 5+ years of direct experience building power dispatch models (SCUC/SCED) using optimization solvers (Gurobi, CPLEX, etc.) Knowledge of power plant dispatch, grid operations (including capacity and AS obligations), and LMP pricing in US power markets Experience using SQL and time‑series databases Proficiency in Python and Git; additional experience with an OOP language a strong plus Domain knowledge in ERCOT, PJM, or CAISO preferred Benefits The annual base salary range for this role is $150,000-$250,000 (USD), which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. #J-18808-Ljbffr