At a Glance
- Tasks: Develop and optimise mathematical models for trading in diverse commodity markets.
- Company: Join a top-tier macro hedge fund in London with a collaborative culture.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a fast-paced environment.
- Why this job: Make a real impact on investment decisions using advanced quantitative research.
- Qualifications: Master’s or PhD in a quantitative field and strong programming skills required.
The predicted salary is between 80000 - 100000 £ per year.
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.
Commodity Quantitative Analyst in London employer: Camber Morris - Quantitative Talent
At Camber Morris, we pride ourselves on being an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. Our hybrid model fosters a culture of teamwork and flexibility, allowing our Commodity Quantitative Analysts to thrive while developing cutting-edge models that influence real-world investment strategies. With ample opportunities for professional growth and access to advanced resources, you will be empowered to make a significant impact in the fast-paced world of macro hedge funds.
Contact Details:
Camber Morris - Quantitative Talent Recruitment Team
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