Quantitative Power Trading Analyst

SaltHill Group Inc. is seeking a Quantitative Power Trading Analyst in Chicago, IL, to optimize renewable power generation assets. Responsibilities include market forecasting, model back-testing, risk analysis, and developing trading strategies for wind, solar, and battery storage. Candidates should have a relevant bachelor's degree, 1-5 years of experience in energy markets, and strong skills in Python and SQL. This is a full-time position.
A global energy trading firm in Chicago seeks an experienced Power Trading Analyst with quantitative research and modeling skills to optimize its renewable power generation assets. This position is part of the commercial operations team responsible for speculative and asset trading, including dispatch, optimization, and hedging a sizeable renewable power portfolio consisting of utility-scale wind, solar, and battery storage generation.

Responsibilities include:
• Daily forecasting of the market prices and risks for the company's renewable power portfolio and OTC markets.
• Back-testing models,
• Modeling and identifying risks and opportunities in the power markets using statistical and fundamental analyses,
• Developing and optimizing the trading activities within CAISO, ERCOT, MISO, NEISO, NYISO, PJM, and SPP in the short term (prompt up to a month ahead),
• Developing and operating short-term strategies for integrated wind, solar, and battery storage portfolios,
• Proposes hedging strategies to optimize these assets and minimize risks, and
• Developing, testing, and implementing new tools to be used by the trading team.

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 1-5 years of professional experience in quantitative research, modeling, and analysis in the energy markets.
• Industry experience in energy trading, conventional/renewable power, natural gas, or crude oil. A variety of analytic experiences will be considered.
• 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 end trading floor environment.
• Strong communication skills.