- Participate in the design and development of systems including algorithmic orders, quantitative models, and smart order routing, translating algorithmic designs into runnable and verifiable system implementations.
- Participate in the research and optimization of execution algorithms such as TWAP and VWAP, as well as machine learning–based strategies, with a focus on execution performance and result reproducibility.
- Participate in the development and optimization of algorithms and systems related to option pricing and volatility surfaces, with attention to the correctness of pricing logic, parameters, and boundary conditions.
- Make appropriate use of AI tools to improve efficiency in research and development, and validate key outputs such as model results, executions, and pricing.
- Read English technical literature, interface protocols, and relevant market materials, and engage in day-to-day and technical communication with business and engineering teams.
Requirements
- Education: Bachelor's degree or above in Financial Engineering, Computer Science, Applied Mathematics, or a related STEM field.
- Financial knowledge: Familiarity with securities trading mechanisms and a basic understanding of algorithmic execution or option pricing; internship or project experience in quantitative finance, securities firms, exchanges, or fintech is preferred.
- Technical skills: Solid programming fundamentals; proficiency in at least one language such as Python or Go; ability to implement algorithms and models as runnable code; Basic knowledge of machine learning is preferred.
- Work attributes: Respect for financial business, data, and rules; risk awareness and sensitivity to pricing, executions, and anomalous results; clear logical thinking and effective communication and collaboration.
- Language skills: Good English & Chinese listening, speaking, reading, and writing skills; ability to read English technical literature fluently and to communicate in both day-to-day and technical contexts.
- Preferred qualifications: Project or research experience in machine learning, deep learning, or option pricing; hands-on experience applying AI tools to model research or code implementation.
*Open to candidates graduating between January 2026 and August 2027.