A leading hedge fund specialising in commodity derivatives trading is seeking a highly skilled Quantitative Researcher with strong expertise in artificial intelligence and machine learning. This role will focus on processing and analysing large, complex datasets to generate actionable insights that directly inform trading strategies across global commodity markets.
Key Responsibilities
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Design, implement, and optimise AI/ML models to identify trading opportunities and market inefficiencies in commodity derivatives.
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Develop scalable tools and pipelines for ingesting, cleaning, and analysing structured and unstructured market data.
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Conduct deep research into historical and real-time market behaviour to enhance predictive modelling and signal generation.
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Collaborate closely with traders, risk managers, and technologists to translate research outputs into profitable trading strategies.
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Monitor model performance and adapt algorithms to evolving market conditions.
Requirements
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Advanced degree (MSc/PhD) in a quantitative discipline (e.g. Computer Science, Statistics, Mathematics, Financial Engineering).
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Proven track record applying AI/ML techniques (e.g. deep learning, NLP, reinforcement learning) to large and complex datasets.
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Strong programming skills in Python, with experience in relevant libraries (e.g. TensorFlow, PyTorch, Scikit-learn).
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Solid understanding of financial markets, preferably commodities and derivatives.
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Experience working in a high-performance trading or investment environment is highly advantageous.