Quantitative Developer – Execution

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Description

Key Responsibilities Full-Lifecycle Implementation: Participate in the full lifecycle of quantitative strategy implementation, including research, code optimization and deployment, order execution, policy compliance, and risk control. Research Tooling & Backtesting: Work closely with the research team to design and develop strategy research tools on our in-house backtesting platform, tailored to their specific use cases. Production Ownership: Take ownership of the development and maintenance of live trading processes, continuously improving the production quality and reliability of strategies through robust technical solutions. Infrastructure Collaboration: Collaborate with the engineering team to shape and implement core components of our distributed systems, data platforms, and trading infrastructure—your contributions will directly impact both research and live trading performance. Algo Optimization: Partner with the research team to iterate on execution features, translating mathematical models and signals into high-performance, low-latency code across global equity and futures markets. Required Qualifications & Skills Strong Programming Foundations: Proficient in Linux environments, Production-level experience in C++ (modern standards) for low-latency components and Python for data analysis, rapid prototyping, and framework development. Domain Expertise: Solid understanding of equity and futures markets , including market microstructure, order book dynamics, and electronic execution logic. , backtesters, data pipelines, simulation environments, or analytics engines). Mathematical/Quantitative Literacy: Comfortable with statistics, data analysis, and evaluating the mathematical logic behind execution signals and performance metrics. Communication & Collaboration: Exceptional ability to translate concepts between highly academic researchers, strict system engineers, and fast-paced production traders. Preferred/Nice-to-Have Outstanding performance in competitive programming contests such as NOI or ICPC. Experience with distributed systems, high-performance computing (HPC), or handling large-scale tick data. , FIX, native exchange APIs). Publications in top-tier CS or Statistics journals/conferences. Award-winning participant in Kaggle machine learning competitions. Internship or work experience in proprietary trading firms, hedge funds, or leading tech companies.

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