Senior Quantitative Specialist – Commodities (London)

We are working with a global hedge fund that are expanding their commodities division and looking for a Senior Quant to work closely with both investment and risk teams to design, refine, and implement models that underpin commodity trading strategies and the broader growth of the business.

Key Responsibilities

• Design and deploy valuation frameworks for complex commodity derivatives and bespoke structured deals.

• Build and enhance modelling approaches used to assess risk in commodity markets, including methodologies for curve construction and volatility surface generation.

• Upgrade and expand the existing suite of risk reporting tools, spanning P&L attribution, portfolio diagnostics, and other regular or on‑demand analyses.

• Develop techniques for both backward‑looking and hypothetical stress-testing, and interpret the outputs using consistent quantitative measures.

• Collaborate with Risk Management to calibrate, configure, and improve risk systems.

• Apply quantitative techniques to issues such as liquidity assessment, cost‑to‑liquidate estimates, and other market‑risk topics.

• Support the broader firm‑wide risk group by contributing commodity‑related insights and occasionally performing analysis on non‑commodity portfolios or assessing cross‑portfolio interactions.

• Provide input to the Global Risk Committee on key market drivers and emerging risks across relevant sectors.

• Partner with Technology to automate workflows and ensure research tools and reporting engines integrate seamlessly with existing platforms.

• Assist in onboarding new products and portfolios from a risk analytics perspective.

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Required Qualifications

• More than a decade of experience in a commodities‑focused quant, strategy, or quantitative risk role at a trading house, bank, hedge fund, utility, or similar institution.

• Advanced academic training (Master’s/PhD) in a quantitative discipline such as mathematics, physics, engineering, statistics, finance, or economics.

• Expertise in modelling and valuing physical commodity assets and structured products, including storage, power tolling, transmission, and comparable structures.

• Strong background in quantitative support for complex commodities trading books, including portfolio construction and optimisation.

• Familiarity with multiple commodity markets (ideally across regions): power, congestion, natural gas, crude, refined products, energy assets, agriculture, structured trades, shipping, etc.

• Understanding of seasonality effects in commodity‑specific risk models.

• Proficiency in Python and SQL, with solid experience using numerical libraries such as NumPy and pandas.

• Demonstrated analytical, problem‑solving, and communication strengths, with the ability to work effectively in a collaborative environment.

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Preferred Skills

• Advanced Python capabilities (virtual environment management, packaging/release workflows, multiprocessing, etc.).

• Experience building dashboards or visual tools, particularly using Plotly Dash.

• Background in hedge funds or asset managers with exposure to factor analytics or systematic futures strategies.

• Experience with fundamental modelling approaches.

• Knowledge of machine learning techniques, PCA, factor decomposition methods for risk and P&L, and related quantitative techniques.