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Manager, Power Marketing – Renewable Fundamentals

Remote / Houston, TX

Our client is a national utility-scale solar + storage developer with ~9GW of projects across North America. We’re looking for a Power Marketing expert to help shape our client’s commercial branch of the company, and drive growth by leveraging a strong understanding of the US power markets, quantitative analysis, PPA structures, and load forecasting. The ideal candidate will bring deep knowledge of the utility sector, experience designing LMP forecast models, and a strong track record of managing offtake opportunities.

Key Responsibilities:

  • Manage the market analysis and fundamentals arm of the organization, including production cost modeling, nodal basis risks, and merchant nodal pricing.
  • Provide market insights and customized analysis in North America power markets including ERCOT, PJM, MISO, NYISO, and WECC based on experiences and knowledge of market fundamentals, resources mix and regulatory initiatives
  • Conduct in-depth analysis of Utility IRPs, renewables requirements, forward pricing, and purchased power, leveraging advanced data analytics to uncover insights and assist our development team in identifying project development prospects.
  • Assist the commercial analytics division in constructing data analytics models using tools such as Matlab, R, Python, and Excel.
  • Support our corporate finance team, aiding in pricing support, energy storage modeling (BESS), and enhancing financial models to incorporate nodal price forecasts.

Preferred / Desired Qualifications:

  • Bachelor’s degree in a quantitative field, such as Economics, Engineering and Environmental Science.
  • 4-6 years of experience in power marketing, power trading, market fundamentals, quantitative analysis etc.
  • Experience working commercial production cost and capacity expansion modeling software: PSO/Enelytix, PLEXOS, ProMOD, Gridview, Aurora, GE MAPS, Dayzer, etc.
  • Sophisticated data management and statistical analysis skills (Excel, Power BI, R and Python).
  • Solid understanding of utility rate structures and quantitative modeling as it relates to electric utility or solar project finance preferred.

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