Quantitative Developer

Our client is a proprietary trading firm specialising in systematic and high-performing discretionary strategies across multiple asset classes. The firm leverages advanced technology, quantitative research and sophisticated models to capitalise on opportunities in global markets., Our client is seeking a talented and driven Quantitative Developer to join its trading technology team. The role focuses on developing and enhancing the research infrastructure supporting quantitative systematic strategies, alongside the production-level development and optimisation of quantitative strategies, primarily across futures and other derivatives., n \n

• Research Infrastructure and Tooling: Build and maintain research pipelines and tools for data sampling, quantitative analysis, simulation, backtesting and post-trade analysis to support the assessment and monetisation of live trading performance. \n

• Platform Integration: Develop and integrate quantitative systematic strategies, migrating them from the research environment to the production trading platform. \n

• Execution Systems: Develop and maintain low-latency trading execution systems across equities, derivatives and digital assets. \n

The ideal candidate will have a strong foundation in C++ and/or Python, a sound understanding of market microstructure and a passion for building high-performance trading infrastructure.

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Our client values individuals who are passionate about innovation and solving complex problems. This opportunity offers the chance to make a meaningful impact, contribute to the development of advanced trading technology and take quantitative strategies to the next level., * Strategy Experience: A proven track record of working with fully systematic high-frequency trading (HFT) or medium-frequency trading (MFT) strategies, including backtesting and execution. \n

• Programming Skills: Proficiency in C++ and Python, with an emphasis on developing systematic research tools, implementing quantitative systematic strategies in production environments and optimising performance. \n

• Industry Experience: At least three years of relevant experience, with a strong understanding of systematic strategies, market microstructure, order types and execution venues for futures markets, particularly CME. \n

• Academic and Analytical Background: Expertise in mathematics, statistics or computer science, supported by strong numerical programming skills and experience with libraries such as NumPy and SciPy. \n

• Quantitative Techniques: Experience with statistical modelling, signal processing or machine learning applied to trading systems would be advantageous. \n