Quantitative Trading & Research — eTrading Associate

JPMorganChase; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

J.P. Morgan in London seeks an Associate/VP for the Quantitative Trading & Research Equity eTrading team. You will design and improve algorithmic execution strategies and develop advanced quantitative models, collaborating with Electronic Client Services to tailor research results for clients.

You will work with large-scale datasets, validate models, and translate research into measurable performance improvements, leveraging Python and kdb+/q in a global setting.

Qualifications

• Master's degree or PhD in STEM or equivalent practical experience.
• Relevant experience in quantitative research, electronic trading, or related fields.
• Advanced knowledge of mathematics and statistics (probability theory, time series, econometrics, causal inference).
• Strong programming skills in Python and/or kdb+/q, with experience with large-scale trading and market datasets.
• Strong analytical, quantitative, and problem-solving skills, with excellent written and verbal communication.

Responsibilities

• Research and model development: conduct market microstructure research and quantify impact on execution outcomes and product design.
• Analyze large datasets to extract stable causal relationships and signal structures.
• Back-test methodologies to ensure robustness and reproducibility.
• Lead development of analytics and data-driven processes to automate model calibrations.
• Collaborate with Technology to industrialize research into production-ready capabilities and governance.

Skills

Python

kdb+/q

Quantitative research

Statistics

Time series

ML basics

Education

Master's degree or PhD in STEM

Tools

AWS

Job description

J.P. Morgan in London seeks an Associate/VP for the Quantitative Trading & Research Equity eTrading team. You will design and improve algorithmic execution strategies and develop advanced quantitative models, collaborating with Electronic Client Services to tailor research results for clients.

You will work with large-scale datasets, validate models, and translate research into measurable performance improvements, leveraging Python and kdb+/q in a global setting.