Data Analyst – Power Market Modeling

RESPONSIBILITIES

• Deliver fast, high-quality data analysis in Excel and Python to meet time-sensitive power market modeling and reporting needs.
• Perform power market modeling and long-term price, nodal basis, and curtailment forecasting.
• Use production cost modeling tools such as Hitachi PROMOD to simulate future power markets and provide price forecasting
• Build and maintain a suite of in-house software tools and data pipelines for energy market analysis using Excel, Python, and/or other programming languages.
• Model and evaluate the impact of market design changes and topological changes, such as new generation, new storage, and transmission line buildouts on future energy prices.
• Communicate clearly and succinctly with audiences of different backgrounds during meetings and presentations.

REQUIRED QUALIFICATIONS

• Bachelor of Science in Electrical Engineering (Power Systems), Computer Science, Data Science, Operations Research, Economics, Math, or other quantitative fields of study.
• Must be highly proficient and fast in Excel and Python-based data analysis, including the ability to perform real-time calculations (e.g., lookups, formulas, scripts).
• Strong background in power markets with a solid understanding of pricing mechanisms, market structures, and key components is required.
• Relevant work experience in the power industry (e.g., ISO/RTO, utilities, energy trading firms, software vendors, or consulting) is preferred.
• Experience with production cost modeling software such as PROMOD, Aurora, and PLEXOS is a plus.
• Proficiency with modeling the transmission network in a commercial production cost modeling / SCED / power flow software tool is a plus.
• Coursework in at least one of the following areas: power system analysis, power system economics, power markets, or power system operations and planning. Relevant work experience may be considered as a substitute for coursework.