J.P. Morgan Asset Management is a leading investment manager for institutions, financial intermediaries and individual investors worldwide. It offers investment management across all major asset classes including equities, fixed income, alternatives, multi-asset and money market funds.

 

This is an exciting opportunity to join J.P. Morgan Asset Management’s Global Trading Analytics and Strategy team. The team focuses on quantitative analysis of trading outcomes, while also contributing to the development of execution strategies and day-to-day support of the trading process.

 

As a Trading Analytics and Strategy Vice President/ Associate on the team, you will be involved in delivering trading research that improves execution outcomes and building analytics and tools that support the trading process.

 

Job responsibilities:

• Deliver trading research projects that improve the investment and execution process.

• Partner with traders and technology teams to design, build, and roll out systematic trading strategies and tools.

• Develop and enhance analytics, dashboards, and monitoring processes to evaluate broker, trader, and strategy performance.

• Own the stability and ongoing enhancement of the APAC analytics platform, including key data inputs such as OMS/EMS feeds and market data services.

 

Required qualifications, capabilities and skills:

• Bachelor’s degree in a quantitative or finance-related discipline (e.g., Computer Science, Statistics, Mathematics, Engineering, Economics, or Finance).

• 4+ years of experience in trading analytics / execution analytics / quantitative research / electronic trading / TCA (or a closely related markets role with strong data/quant focus).

• Professional experience in coding (Python and/or R) and strong SQL skills.

• Familiarity with OMS/EMS data models and execution workflows across platforms, with a solid understanding of APAC equities market microstructure.

• Strong communication skills, with the ability to present findings clearly to traders and senior stakeholders, and product ownership experience to translate trading needs into requirements and delivery.

 

Preferred qualifications, capabilities and skills:

• Experience with machine learning and statistical modeling techniques.

• Prior experience working effectively in a globally distributed team.