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Quantitative Researcher, Equity

Exclusive opportunity

Onsite

Quantitative Researcher, Equity

Millennium

Quantitative Researcher, Equity

Skills

Python

2 months ago

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Important information


Contract type:

Permanent

Location:

Hong Kong

Work mode:

Onsite

Published on:

10 August 2026

What they need


Quantitative Researcher as part of a collaborative London-based team, with a focus on systematic equity strategies. Preferred Location: Asia office (Singapore, Hong Kong, Tokyo) Principal Responsibilities **Working alongside the SPM on alpha research, with a primary focus on: idea generation, data gathering and research/analysis, model implementation and backtesting for systematic equity strategies - typically approaching ideas from an Asian perspective, but applying them globally

Combine sound financial insights and statistical learning techniques to explore, analyze, and harness a large variety of datasets in order to build strong predictive models which will be deployed to the investment process

Continuously fine tune Asia portfolio's optimization

Conduct risk analysis of live performance and pnl attribution

Handling live trading operations in Asia market including failed orders, futures trading/rolling.** Preferred Technical Skills **Strong research and programming skills in Python are necessary

Masters or PhD degree in a quantitative subject such as Computer Science, Applied Mathematics, Statistics, or related field from a top ranked university** Preferred Experience **1-3 years of experience with cash equities strategies doing alpha research

Experience with trading in Asian markets. Familiarity with Asia market's distinctive characteristics such as stamp cost, financing, no short constraints etc is preferred.

Demonstrated ability to understand fundamental and event related data and experience with alternative data sources** Highly Valued Relevant Experience **Strong economic intuition and critical thinking

Product experience in statistical arbitrage strategies** Target Start Date As soon as possible

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