- Hong Kong Hong Kong
Eka Finance Hiring! Full Time Quant Analyst - Machine Learning Focus - Asia in Hong Kong - Ricebowl
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Job Description
Responsibilities
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
- Generate predictive features from high-frequency market data as well as alternative and unstructured datasets for use in ML models
- Build and optimise research pipelines across distributed computing environments, supporting a range of approaches including tree-based methods, deep learning, and NLP/LLM techniques
- Research, design, and implement systematic alpha signals across equities, futures, and other liquid instruments
- Partner with engineering and trading teams to productionise models, monitor live performance, and iterate based on real-world results
- Stay at the forefront of academic and industry developments in machine learning, contributing new ideas and research directions to the team
Requirements
- Master’s or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field from a leading university
- 5+ years of experience in alpha research within a top-tier buy-side firm or global investment bank
- 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
- Proficient in Python, with additional experience in C++ or similar languages preferred; comfortable working with distributed or hybrid compute infrastructure
- Strong communication skills and the ability to operate effectively in a fast-paced, collaborative trading environment
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