Quantitative Researcher
Hong Kong
We are partnered with a fully systematic hedge fund headquartered in Asia. The firm operates a fully quantitative investment platform and is backed by a leading hedge fund with significant institutional capital.
Their core focus is global macro, deploying data-driven, statistically derived signals across liquid markets including rates, FX, commodities, and equity indices. The investment approach combines rigorous research, disciplined risk management, and scalable technology infrastructure.
Due to strong performance over the last 10 years and continued capital inflows, the firm is expanding its centralised research platform and is seeking talented Quantitative Researchers to contribute across macro strategy development.
This is an opportunity to join a high performing team at a pivotal stage of growth, working within a collaborative research environment where alpha generation, innovation, and scientific rigour are at the centre of the investment process.
Relocation assistance and sponsorship provided.
The Role:
- Design and enhance proprietary equity alpha models across global markets, spanning cross-sectional signals, factor frameworks, and catalyst-driven approaches.
- Evaluate corporate fundamentals, balance sheet dynamics, earnings developments, and market structure behaviour to strengthen signal quality and portfolio outcomes.
- Break down portfolio exposures by sector, geography, and investment style to identify performance drivers and sources of downside risk.
- Lead the full quantitative research lifecycle - from idea generation and hypothesis testing through backtesting, validation, and live implementation.
- Work with large-scale financial datasets to uncover statistically robust patterns and evaluate risk-adjusted return characteristics.
- Collaborate closely with trading and technology teams to productionise strategies and continuously optimise execution and monitoring processes.
- Produce ongoing analytics, model diagnostics, and clear documentation to support governance and performance review.
Requirements:
- Advanced degree (Master’s or PhD) in a quantitative discipline such as Mathematics, Statistics, Physics, Engineering, Data Science, or a related field.
- Strong foundation in probability and statistical modelling, including areas such as machine learning, time-series modelling, pattern detection, and natural language processing.
- High proficiency in programming (e.g., Python, C#, MATLAB, SQL) with the ability to build scalable research and backtesting frameworks.
- Demonstrated experience developing and implementing systematic strategies - particularly index rebalancing methodologies - including optimisation, automation, and performance evaluation using quantitative techniques.