A global multi-manager hedge fund is seeking a quantitative researcher to join its systematic trading team in Hong Kong. The firm invests across quantitative, fundamental equity and macro strategies, supported by significant investment in proprietary technology, infrastructure and risk analytics.
About the Role
You will build machine learning driven alpha for liquid markets, working closely with quantitative portfolio managers, developers and fellow researchers to take signals from research through to production. The role sits on the trading floor and is measured on live performance, not research output alone.
Key Responsibilities
- Engineer predictive features from high-frequency market data and unstructured alternative datasets for machine learning models
- Develop research pipelines on a distributed compute cluster for tree-based models, deep learning, NLP and LLM approaches, and related methods
- Design and prototype ML-driven alphas for cash equities, futures and other liquid asset classes
- Collaborate with researchers and developers to deploy signals into production, and iterate on them based on real performance
- Track academic and industry advances in machine learning, and present actionable ideas to the team
Requirements
- MS or PhD in computer science, statistics, mathematics or a related quantitative discipline from a top-tier university
- A minimum of five years of alpha research experience at a leading buy-side firm or global bank
- Expertise in tree-based models, deep learning and NLP or LLM methods, with a strong grasp of probability and of overfitting control in practice
- Proficiency in Python, preferably alongside C++ or similar, with experience of distributed or hybrid compute environments
- Excellent analytical, verbal and written communication skills, with a proactive, ownership-driven mindset suited to a fast-paced trading floor