Quantitative Researcher

About Fuse Energy

Fuse Energy is a renewable power startup focused on accelerating the buildout of clean energy at scale. The company applies first-principles thinking and modern technology to create a more efficient energy system, with the goal of delivering a terawatt of renewable energy as quickly as possible. It has raised $170M from investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group, and strategic backers such as Nico Rosberg, the co-founder of Solana, and partners linked to Meta, Revolut, Spotify, Uber, and more.

The business is building a vertically integrated energy platform that spans solar, wind, and hydrogen project development, live power trading, and distributed energy deployments. By selling straight to consumers, it aims to remove intermediaries, reduce prices, and pass those savings on.

Alongside this, the company is developing the Energy Network, a decentralised system of smart devices that gives users Energy Dollars for electrifying homes, shifting consumption to lower-demand periods, and supporting grid balancing. The network is intended to improve grid reliability, which is especially important for expanding AI data centres and other high-energy industries.

Responsibilities

• Create and maintain quantitative models that support hedging approaches for retail energy supply.
• Study market data to improve how physical assets such as solar and wind farms perform.
• Use statistical and scenario-based techniques to guide trading and risk decisions.
• Track power market movements, price patterns, and regulatory changes to surface risks and opportunities.
• Work closely with engineering and operations teams so models can be used in everyday decision-making.

Requirements

• At least 1 year of experience in quantitative modelling, data analysis, or a similar role within energy, trading, or analytics.
• Strong Python skills, including practical use of data analysis, modelling, and visualisation libraries.
• A solid grasp of statistics, optimisation, and analytical methods.
• Experience handling time-series or market data, ideally from energy or commodities markets.
• Good problem-solving ability and the capacity to turn complex data into clear, practical recommendations.

Benefits

• Competitive pay plus an equity sign-on bonus.
• Biannual bonus programme.
• Company-provided tech tailored to your needs.
• Paid annual leave.
• Breakfast and dinner support for employees working from the office.