Quantitative Researcher

Overview

In this role you will build and implement quantitative models to support hedging and trading for retail energy. You will work closely with engineering and operations to embed models into daily decision-making and improve asset performance. You’ll monitor market data, pricing, and regulatory developments to identify risks and opportunities that shape strategy. The role offers a hands-on chance to shape risk management and trading outcomes at a fast-growing renewables startup. This is a data-driven, cross-functional environment focused on scalable energy solutions and grid balance.

Pay / Benefits

• competitive salary
• equity sign-on bonus
• biannual bonus
• fully expensed tech
• paid annual leave
• breakfast and dinner allowance

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

Key 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

• collaboration across cross-functional teams
• analytical thinking
• proactive problem-solving
• Python
• statistical modeling
• time series analysis

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