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Fuse Energy is a well-funded energy startup ($200M+ raised from top-tier investors including Balderton, Accel, Lakestar, and others) building an integrated energy company that combines solar, batteries, grid infrastructure, real-time power trading, and distributed energy solutions for consumers. The company uses AI across operations and sells directly to consumers to reduce costs.
As a Quantitative Researcher, you will develop and implement quantitative models that power the company's trading, hedging, and physical asset optimization strategies. Your work will directly support critical business decisions across the energy trading and operations functions.
Key responsibilities include:
- Developing and implementing quantitative models to support hedging strategies for retail energy supply
- Analyzing market data to optimize performance of physical assets such as solar and wind farms
- Conducting statistical and scenario-based modeling to inform trading and risk management decisions
- Monitoring power markets, pricing trends, and regulatory developments to identify risks and opportunities
- Collaborating with engineering and operations teams to integrate models into day-to-day decision-making
This is an individual contributor role focused on model development and data analysis rather than team management.
Requirements:
- 1+ years of experience in quantitative modeling, data analysis, or a related role in energy, trading, or analytics
- Strong proficiency in Python, with experience using libraries for data analysis, modeling, and visualization
- Solid understanding of statistical modeling, optimization, and analysis techniques
- Experience working with time series or market data, preferably in energy or commodities markets
- Strong problem-solving skills and the ability to translate complex data into actionable insights
