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.
System Design & Architecture: Experience contributing to or designing complex frameworks (e.g., 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.
Familiarity with connectivity protocols (e.g., 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.
