ABOUT THE ROLE
The FTR Developer will contribute to research, modeling, and system development in nodal independent system operator (ISO) markets. The role focuses on building, maintaining, and improving advanced models that capture renewable generation impacts, grid congestion, and electricity market dynamics to identify trading opportunities.
This position is ideal for someone with strong quantitative, programming, and problem-solving skills who thrives in a dynamic, collaborative environment where their work directly influences commercial outcomes. Attention to detail, model quality, and transparent communication are essential.
RESPONSIBILITIES
Build and manage models to analyze renewable generation projects, power flows, and electricity price forecasting
Conduct research and modeling of electricity supply, demand, and congestion fundamentals for daily trading and long-term assessments
Maintain, execute, and calibrate power flow optimization models
Collaborate with the team to implement systematic congestion analysis and forward valuation using OPF and nodal simulation tools
Maintain the Production Cost Model, incorporating market and in-house perspectives
Develop and maintain codebases for automated reporting, dashboards, and data visualization of risks and opportunities
Perform quantitative and econometric studies of energy markets, generation, and transmission projects
Track, analyze, and communicate electricity market fundamentals clearly and efficiently
Mine and analyze large datasets to identify commercial opportunities
QUALIFICATIONS
Bachelor’s degree in Mathematics, Economics, or related quantitative discipline
Minimum of one year of experience in electricity markets in consulting, commercial, engineering, or ISO role
Proficiency with nodal market simulation or OPF tools such as PowerWorld, PROMOD, UPLAN, GridView, GE MAPS, DAYZER, PLEXOS, or Aurora
Ability to work effectively in a fast-paced, team-oriented environment and follow projects through to completion
Strong quantitative and research skills with the ability to test hypotheses and adapt based on incomplete information
PREFERRED QUALIFICATIONS
Master’s or PhD in Electrical Engineering, Economics, Mathematics, Physics, or other quantitative discipline
Proficiency in Python, Visual Basic, Matlab, R, SQL, or similar analytical tools
Advanced skills in simulation, optimization, statistics, and/or options pricing theory
Experience with machine learning, data science techniques, and regression/classification models
Familiarity with databases/warehouses such as Snowflake
Experience with industry data platforms such as YES Energy
Proficiency with Tableau, Power BI, or other business intelligence tools
Knowledge of software engineering practices such as unit testing, source control, and code review
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