Commodity Quantitative Analyst

Alfa AI; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Camber Morris is seeking a brilliant Commodity Quantitative Analyst to join a top-tier macro hedge fund in London. In this hybrid role, you will develop mathematical models and systematic strategies that drive investment decisions.

You will work on data exploration, backtesting, risk analysis, and platform improvements to support real-time market analysis. The position combines rigorous research with practical trading execution in a collaborative environment, offering high visibility and impact

Qualifications

• Master’s degree or PhD in a highly quantitative discipline (math, physics, quantitative finance, or computer science).
• Proficient coding in Python, C++, or R with production-grade code and data libraries.
• 3+ years of experience as a quantitative analyst in a hedge fund, prop trading firm, or investment bank.
• Strong knowledge of time-series analysis, machine learning, and stochastic calculus for financial markets.
• Analytical, detail-oriented, able to explain complex quantitative concepts to non-technical stakeholders.

Responsibilities

• Model development, pricing, analysis and trading across commodity markets (energy preferred).
• Backtest and refine systematic trading strategies for profitability and risk-adjusted returns.
• Source, clean and structure non-traditional data (shipping telemetry, satellite imagery, weather).
• Develop risk frameworks to stress-test positions against macro shocks and liquidity constraints.
• Enhance proprietary research platform for scalable, real-time market analysis.

Skills

Quant degree

Python/C++/R

3+ yrs exp

Time-series ML

Analytical mindset

Education

Master’s or PhD in quantitative field

Job description

Camber Morris are looking for a brilliant Commodity Quantitative Analyst to join a top tier macro hedge fund in London. Joining our elite macro hedge fund team in London, you will step into a high-impact role where your mathematical models and systematic strategies will directly drive investment decisions. Operating on a hybrid model that balances collaborative in-office strategy sessions with remote focus time, this permanent position offers the chance to sit at the absolute intersection of advanced quantitative research and real-world macroeconomic shifts.

Key Responsibilities

• Model Development & Optimization: Design, build, and implement sophisticated mathematical models to price, analyse, and trade across a diverse range of commodity markets (energy preferred).
• Alpha Generation: Formulate, backtest, and refine systematic trading strategies, translating complex data sets into highly profitable, risk-adjusted trading signals.
• Alternative Data Exploration: Source, clean, and structure non-traditional data sets—such as shipping telemetry, satellite imagery, and weather patterns—to gain a predictive edge in physical commodity flows.
• Portfolio Risk Analysis: Collaborating closely with portfolio managers, develop robust risk management frameworks to stress-test positions against macroeconomic shocks and liquidity constraints.
• Infrastructure Advancement: Enhance Camber Morris's proprietary quantitative research platform, ensuring our codebase is scalable, fast, and optimised for real-time market analysis.

Required Skills & Experience

• Advanced Academic Background: A Master’s degree or PhD in a highly quantitative discipline, such as Mathematics, Physics, Quantitative Finance, or Computer Science.
• Programming Mastery: Exceptional coding skills in Python, C++, or R, with a proven track record of writing clean, production-grade code and utilising advanced data science libraries.
• Commodities Expertise: At least 3 years of experience as a quantitative analyst within a hedge fund, proprietary trading firm, or investment bank, with a deep understanding of commodity derivatives, curves, and physical market dynamics.
• Statistical Rigor: Strong knowledge of time-series analysis, machine learning algorithms, and stochastic calculus applied to financial markets.
• Analytical Mindset: A sharp, detail-oriented approach to problem-solving, with the ability to articulate complex quantitative concepts to non-technical stakeholders.

Nice-to-Have

• Prior experience working specifically within a global macro investment mandate.
• Familiarity with cloud computing environments (AWS or GCP) and handling massive, unstructured data pipelines.
• Knowledge of global regulatory frameworks impacting physical and derivative commodity trading.