Quant Researcher, Power Dispatch Modeling

Point72; New York (NY); On-site; USD 150,000 - 250,000; Full time

Job summary

Point72 in New York seeks a Quant Researcher to build, run, and refine a power dispatch model for ERCOT and other major US ISOs, reporting to a Stamford-based PM.

You will drive model inputs, test against historical data, and communicate results to the investment team, focusing on forward scenario analysis and reducing forecast error.

Requires a Master’s/PhD in a quantitative field and 5+ years in power dispatch modeling, with strong Python, Gurobi/CPLEX, SQL, and ERCOT/PJM/CAISO knowledge.

Qualifications

• PhD or Master's in a quantitative field; 5+ years building power dispatch models (SCUC/SCED) using optimization solvers.
• Strong knowledge of power plant dispatch, grid operations, and LMP pricing in US power markets.
• Experience with SQL and timeseries databases; proficiency in Python and Git; OO language is a plus.

Responsibilities

• Formulate, build, and run a power dispatch model using Python and a commercial solver.
• Collaborate with PM to optimize inputs and architecture of the model.
• Ensure the model replicates historical grid operations and analyzes forward scenarios.
• Communicate results and limitations to the investment team; publish results to dashboards.

Skills

Power dispatch modeling

Optimization

ERCOT/PJM/CAISO domain knowledge

Python

Git

SQL

Timeseries databases

Education

Master's or PhD in Operations Research / Electrical Engineering / Applied Mathematics

Tools

Gurobi

CPLEX

Job description

Role/Responsibilities

The Quant Researcher will report to a Stamford based Portfolio Manager and will focus on:

• 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

Responsibilities

• 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 timeseries databases
• Proficiency in Python and Git; additional experience with an OOP language a strong plus
• Domain knowledge in ERCOT, PJM, or CAISO preferred

About Point72

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry's brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

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.