Houston, TX

An international energy company in Houston seeks an experienced Quantitative Power Trading Analyst with quantitative research and modeling skills to optimize its power generation assets (thermal and renewable power portfolio). This position is part of the commercial operations team responsible for supporting and executing commercial decisions, including asset trading, dispatch, optimization, hedging, fuel procurement, asset operations, and M&A activities. Generation assets are primarily in the PJM, ISO-NE, NYISO, MISO, and ERCOT markets.

 

With guidance from the Head of Power Trading and Senior Traders, analyze the power markets systematically to support generation asset trading and optimization. Key responsibilities include to:

 

  • Build analytic infrastructure in Python, which includes forecasting models, back-testing and validating modeling approaches, sensitivity analysis, trader tools, and third-party market research
  • Daily forecasting of the market prices and risks for the company’s generation power portfolio and OTC markets
  • Identify asset and power market trading risks and opportunities
  • Analyze and optimize the trading activities within PJM, ISO-NE, NYISO, MISO, and ERCOT (Day-Ahead Real-Time, Cash and Term markets)
  • Help with a short-term strategy for a wind asset
  • Propose hedging strategies to optimize assets and minimize risks
  • Summarize themes and strategies of suggested trades versus the overall portfolios and broader power market

 

Educational and professional requirements include:

 

  • Bachelor’s degree (an advanced degree is a plus) in an applied quantitative field (mathematics, physics, computer science, engineering, or statistics)
  • Approximately 1-7 years of professional experience in quantitative research or quantitative risk in the energy markets (required)
  • Industry experience in energy trading, conventional/renewable power, and/or natural gas
  • Excellent Python programming skills and advanced knowledge of SQL
  • A strong background in linear regression, probability, scenario modeling, statistics, time series analysis, and optimization modeling techniques to data to identify signals and predictive patterns
  • Ability to write and optimize database queries to extract and analyze large data sets
  • A commercial mindset and desire to work within a fast-paced energy trading floor environment
  • Strong communication skills

 

Submit resumes to chynes@salthillgroup.com.