Quantitative Power Trader (Virtuals)
We recently partnered with a prop power trading firm that is looking to bring on Quantitative Researchers and Traders as they look to rapidly expand the business. The firm is a fully systematic group that operates within the Day Ahead Virtual markets across MISO, ERCOT, and SPP. While headquartered in California, the entire company sits remote across the US.
Responsibilities:
- Design, backtest, and implement systematic trading strategies for day-ahead virtuals in MISO, ERCOT, and SPP.
- Leverage historical market data, congestion patterns, and fundamental drivers to identify profitable trading opportunities.
- Monitor and refine strategies based on performance metrics and evolving market conditions.
- Conduct deep analysis of nodal pricing, transmission constraints, load forecasts, and generation patterns.
- Develop and maintain robust Python-based analytics pipelines and automated trading infrastructure.
- Work closely with fellow traders, analysts, and developers to share insights and improve strategy performance.
Qualifications:
- Bachelor's or Master's degree in Engineering, Mathematics, Computer Science, or a related quantitative field.
- 3+ years of experience in power trading or alpha generation, with a focus on day ahead virtuals in MISO, ERCOT, or SPP.
- Strong programming skills in Python
- Deep understanding of ISO market mechanics, LMP formation, and congestion modeling.
- Experience with machine learning, statistical modeling, or optimization techniques is a plus.
- Excellent problem-solving skills and attention to detail.
- Ability to thrive in a fast-paced, data-driven trading environment.
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