Quant Risk Analyst - FTR, Gas and Power Risk

A leading global hedge fund is seeking an exceptional Quantitative Researcher to support its Commodities Risk function. In this role, you will partner closely with risk managers, technologists, and investment professionals to design and implement models that advance trading, risk measurement, and physical commodities analytics across the platform.

• Develop and implement quantitative models for analysing commodity derivatives and physical markets, including methodologies for term-structure construction and volatility surface modelling.
• Enhance existing risk tools and reporting frameworks covering areas such as risk analytics, P&L attribution, portfolio construction, and both scheduled and ad‑hoc reporting.
• Build methodologies for historical and hypothetical stress testing and interpret results using robust statistical metrics.
• Calibrate and configure risk systems in collaboration with risk management stakeholders.
• Apply quantitative approaches to assess market liquidity, transaction costs, and other risk‑related challenges.
• Provide analytic support across the broader risk organisation, including cross‑asset portfolio reviews or assessing commodity exposure impacts on firm‑wide risk.
• Contribute insights on market structure, risk drivers, and relevant developments to senior stakeholders.
• Work with engineering teams to automate and integrate research outputs and reporting capabilities into the firm’s core systems.
• Support onboarding of new portfolios, products, and trading strategies.

• 10+ years of experience as a commodities‑focused quant, strategist, or quantitative risk professional within a hedge fund, investment bank, or physical energy trading institution.
• Deep expertise in US FTR, natural gas, and power markets, including extensive experience supporting FTR trading.
• Strong academic background (Master’s or PhD) in a quantitative discipline such as mathematics, physics, engineering, statistics, economics, or finance.
• Proficiency in modelling and valuing physical commodity assets and structured transactions (e.g., gas/oil storage, power tolling, transmission rights).
• Experience across multiple commodity sectors—electricity, natural gas, crude oil, refined products, energy assets, agriculture, structured deals, or shipping.
• Familiarity with seasonality dynamics and how they are incorporated into commodity risk models.
• Strong programming skills in Python and SQL, including proficiency with numerical libraries (pandas, Num Py, etc.).
• Excellent analytical problem‑solving capabilities and the ability to communicate complex concepts clearly.
• Collaborative mindset and ability to work effectively with diverse teams.

• Advanced Python proficiency (virtual environments, release workflows, multiprocessing).
• Experience building Plotly Dash applications or other data‑visualisation‑driven tools.
• Previous experience at a hedge fund or asset manager, ideally with exposure to systematic futures or portfolio construction.
• Familiarity with factor analysis, PCA, P&L and risk decomposition models, or machine‑learning techniques.