The Role

We are looking to hire an experienced Quantitative Researcher to join a high-performing systematic trading team based in Hong Kong. This is a hands-on research role focused on developing and deploying machine learning-driven trading signals across liquid markets.

You will work in close collaboration with Portfolio Managers, researchers, and engineers to build scalable research frameworks and translate cutting-edge ideas into live trading strategies.

Key Responsibilities

1. Generate predictive features from high-frequency market data as well as alternative and unstructured datasets for use in ML models
2. Build and optimise research pipelines across distributed computing environments, supporting a range of approaches including tree-based methods, deep learning, and NLP/LLM techniques
3. Research, design, and implement systematic alpha signals across equities, futures, and other liquid instruments
4. Partner with engineering and trading teams to productionise models, monitor live performance, and iterate based on real-world results
5. Stay at the forefront of academic and industry developments in machine learning, contributing new ideas and research directions to the team

Requirements

1. Master’s or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field from a leading university
2. 5+ years of experience in alpha research within a top-tier buy-side firm or global investment bank
3. Strong experience across machine learning techniques, including tree-based models, deep learning, and NLP/LLMs, with a solid grounding in statistical modelling and overfitting control
4. Proficient in Python, with additional experience in C++ or similar languages preferred; comfortable working with distributed or hybrid compute infrastructure
5. Strong communication skills and the ability to operate effectively in a fast-paced, collaborative trading environment