Job Description

About Us:
Huatai International Financial Holdings Company Limited (“Huatai International” or “the Company”), is the only overseas wholly-owned or controlled subsidiary of Huatai Securities. Huatai International is the Huatai Group’s international arm which plays as a crucial role in the group's internationalization strategy by:
a) not only providing offshore capital market services (and a global business platform) but also provides onshore clients with valuable cross-border capital market services (aligned with the mainland China government’s policies and commercial intentions);
b) actively making use of Huatai Securities’ leading position, distribution network and customer base in mainland China;
c) integrating on a global basis across many jurisdictions and regions, a successful and fully integrated international financial platform with innovative financial services solutions.

Huatai International operates as a holding company for consolidating all of the group’s cross-border businesses and companies under one umbrella, offering a truly unified and international business platform. In recognition of such international strength, the renowned international rating agency Standard and Poor’s has assigned Huatai International a “BBB+” rating (for long term) and “A-2” (for short-term).

• Design, implement, and optimize quantitative trading strategies using Python (e.g., mean-reversion, momentum, statistical arbitrage, or market-making).
• Conduct rigorous back testing and performance analysis; refine models based on empirical results.
• Monitor live trading systems, diagnose anomalies, and propose improvements.
• Manage and clean large tick/order-book datasets; build robust data pipelines.
• Collaborate with the team on research projects, from idea generation to production deployment.
• Maintain detailed documentation of research, code, and trade logs with high attention to accuracy.

Qualifications:

• Currently pursuing a Bachelor's, or Master's degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or related disciplines.
• Strong programming skills in Python or other programming languages, with experience in writing clean, efficient, and production-ready code.
• Solid understanding of quantitative finance concepts including time series analysis, probability theory, and statistical modeling.
• Hands-on experience designing and back testing systematic trading strategies.
• Experience working with large financial datasets, including data cleaning and pipeline construction.
• Strong analytical mindset with the ability to rigorously evaluate model performance and draw actionable conclusions from empirical results.
• Prior internship or project experience in quantitative research, algorithmic trading, or a related field is highly preferred.