Quantitative Researcher

Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.

We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.

We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.

We're hiring a Quantitative Researcher to build the models behind our trading, hedging and physical asset optimisation.

• →Develop and implement quantitative models to support hedging strategies for retail energy supply
• →Analyze market data to optimize the performance of physical assets such as solar and wind farms
• →Conduct statistical and scenario-based modeling to inform trading and risk management decisions
• →Monitor power markets, pricing trends, and regulatory developments to identify risks and opportunities
• →Collaborate with engineering and operations teams to integrate models into day-to-day decision-making

• 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