High-Frequency Quant Researcher - Market Microstructure

JPMorganChase; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

J.P. Morgan in Hong Kong seeks a quantitative researcher to advance AI Market Lab within the QTR group. You will study microstructure, develop deployable systematic strategies, and work close to live trading environments to translate insights into execution-ready models.

The role emphasizes rigorous experimentation, collaboration with traders and developers, and building measurement and simulation tools to improve performance across venues and regimes.

Qualifications

• Advanced degree or equivalent practical experience in mathematics, statistics, physics, computer science, engineering, or a related quantitative discipline.
• 2+ years of full-time quantitative research experience in high-frequency / medium-frequency trading, electronic market making, or systematic execution.
• Strong programming and data-analysis skills in Python; proficiency in C++ or another high-performance language is highly desirable.

Responsibilities

• Analyze high-frequency market data, including Level 2 and Level 3/4 order-book data, to identify predictive structure and trading opportunities.
• Develop alpha signals and trading features based on order flow, liquidity, and price formation.
• Design, backtest, and implement market-making and risk-taking strategies, including pricing, order placement, and inventory control.
• Develop realistic research and simulation methodologies incorporating latency, fees, rebates, and market impact.
• Optimize strategy performance across signal generation, portfolio sizing, execution, and intraday risk management.
• Collaborate with traders, quantitative developers, technology partners, exchanges, and ECNs to move strategies into production.

Skills

Python

C++

Quantitative research

Data analysis

High-frequency

Education

Advanced degree

Job description

J.P. Morgan in Hong Kong seeks a quantitative researcher to advance AI Market Lab within the QTR group. You will study microstructure, develop deployable systematic strategies, and work close to live trading environments to translate insights into execution-ready models.

The role emphasizes rigorous experimentation, collaboration with traders and developers, and building measurement and simulation tools to improve performance across venues and regimes.