Participate in the full lifecycle of quantitative strategy implementation, including research, code optimization and deployment, order execution, policy compliance, and risk control.
Work closely with the research team to design and develop strategy research tools on our in-house backtesting platform, tailored to their use cases.
Take ownership of the development and maintenance of live trading processes, continuously improving the production quality and reliability of strategies through robust technical solutions.
If you are interested in RL/Optimization-related infrastructure, youll have the opportunity to contribute to relevant research tool development.
Collaborate with the engineering team to shape and implement core components of our distributed systems, data platforms, and trading infrastructureyour contributions will directly impact both research and live trading performance.
Basic Qualifications
Bachelor, Master degree from world top university, majoring in Computer Science, Software Engineering, Mathematics, Physics, Statistics, or other related STEM fields.
Proficient in Linux environments, with strong programming skills in both C++ and Python; comfortable with scientific computing libraries and familiar with common data structures and algorithms.
Solid foundation in mathematics, especially in probability and statistics.
Strong communication skills and logical reasoning abilities.
Comfortable working and communicating in Chinese and English.
Preferred Qualifications
Outstanding performance in competitive programming contests such as NOI or ICPC.
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.
