Energy Modeling Engineer

About the role

You will join the analytics team of an energy company that plans generation portfolios, evaluates market opportunities, and stress-tests investment theses. The team builds the production cost and capacity expansion models that answer the company's biggest questions: what to build, where, and when. This role matters because every major capital decision references your model runs, and the difference between a good model and a great one is measured in basis points on billions of dollars. You will build the simulation models that every major decision depends on, from 8760-hour dispatch models to detailed thermal simulations of building systems. The role demands fluency in both physics and statistics, since calibrated models must match metered data while remaining explainable to non-modelers. You will maintain the team's modeling toolchain, validating new software versions and documenting assumptions so results stay reproducible years later. When model outputs surprise stakeholders, your diagnostic skill will trace the result to the input or interaction that caused it.

What you will achieve

• Deliver production cost model runs covering 50+ GW of market footprint with results validated against historical prices within 5 percent
• Build capacity expansion scenarios that identify the lowest-cost portfolio to meet load growth and policy targets through 2040, with calibration reports showing modeled versus metered variance by end use
• Cut model run turnaround by 40 percent through database optimization, parallel processing, and automated result pipelines
• Own model documentation and assumption registers detailed enough for auditors, regulators, and investors to reproduce results, archived with input files so any result can be regenerated on demand
• Drive insights from model output into plain-language briefings that executives use to approve or reject nine-figure investments

What you will bring

Must-haves

• 2 to 5 years of experience in energy modeling, market analysis, or power systems planning roles
• Strong understanding of electricity market fundamentals: LMP formation, unit commitment, economic dispatch, and capacity markets
• Proficiency with at least one production cost or capacity expansion tool such as PLEXOS, PROMOD, or Aurora
• Advanced Python skills for data processing, scenario automation, and results visualization at scale
• SQL fluency for querying large market, asset, and weather datasets
• Solid grasp of statistics for back-testing models and quantifying forecast uncertainty
• Ability to translate complex model mechanics into clear assumptions and defensible conclusions

Nice-to-haves

• Experience with stochastic modeling or Monte Carlo methods for price and load forecasting
• Knowledge of specific ISO/RTO market rules (PJM, ERCOT, CAISO, or MISO)
• Familiarity with machine learning approaches for load or renewable generation forecasting
• Understanding of transmission modeling and congestion analysis
• Experience with EnergyPlus, TRNSYS, or similar detailed simulation engines