Quantitative Researcher

Description

As a Quantitative Researcher, you will collaborate closely with risk and investment teams to design and implement advanced models for commodity risk analysis. Your work will help optimise risk frameworks and enhance physical trading capabilities across European Gas and Power markets.

• Apply quantitative techniques to assess market liquidity and estimate liquidation costs
• Support risk analytics and reporting processes across the wider risk management function
• Enhance existing risk reporting tools for P&L attribution, portfolio construction, and ad-hoc analysis
• Configure and calibrate risk systems in partnership with Risk Management
• Develop and implement models for risk analysis of commodity products and derivatives, including term structures and volatility surfaces
• Design methodologies for historical and hypothetical stress testing and analyse results using standard statistical metrics
• Assist with onboarding new portfolios and products
• Collaborate with technology teams to automate and integrate research and reporting solutions

Requirements

We are seeking an experienced Quantitative Researcher to join our client’s Commodities Risk Management team. This role reports to the Head of Commodities Risk Analytics and Risk Advisory and will play a key part in developing models and tools that support trading, risk management, and physical commodity strategies.

• Strong skills in valuing and modelling physical commodity assets and structured transactions (e.g., gas storage, power tolling, transmission)
• Expertise in European Gas and Power markets
• Experience incorporating seasonality into commodity risk models
• Excellent problem-solving and communication skills
• Proficiency in Python and SQL, including numeric libraries (pandas, numpy, etc.)
• Advanced academic background (Master’s or PhD) in a quantitative discipline such as Mathematics, Physics, Engineering, Statistics, Economics, or Finance
• Background in hedge funds or asset management with exposure to systematic strategies
• 10+ years’ experience as a commodities quant, strategist, or quantitative risk professional within a physical energy trading environment
• Knowledge of factor analysis, PCA, decomposition models, and machine learning techniques
• Familiarity with a broad range of commodities including electricity, natural gas, crude oil, oil products, and energy assets
• Advanced Python knowledge (virtual environments, release processes, multi-processing)
• Experience with Plotly Dash or other data visualisation tools

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance