Quantitative Researcher

Fuse Energy·London·United Kingdom·Hedge Fund & Quant

Fuse Energy is hiring a Quantitative Researcher in London. Posted 2026-03-04; applications close 2026-08-09 (in 29 days).

Role details

Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy—fast. We are combining first-principles thinking with cutting-edge technology to build a radically better energy system. We have raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group, and strategic angels such as Nico Rosberg, the Co-Founder of Solana, and GPs behind Meta, Revolut, Spotify, Uber, and more. We’re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers. We’re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shift usage to off-peak hours and help balance the grid. This network strengthens grid stability—a critical foundation for scaling AI data centers and other energy-intensive industries.

Responsibilities

  • 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

Qualifications

  • 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

Compensation & Benefits

  • Competitive salary and an equity sign-on bonus
  • Biannual bonus scheme
  • Fully expensed tech to match your needs
  • Paid annual leave
  • Breakfast and dinner allowance for office-based employees

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