Quantitative Risk & Treasury Research Associate (Off-Cycle)

JPMorgan Chase & Co.; Greater London; On-site; GBP 65,000 - 90,000; Full time

Job summary

JPMorgan Chase & Co. in London invites applications for the 2027 Quantitative Research - Risk and Treasury Off-Cycle Associate program.

You will work with senior quants on risk and treasury modeling, applying mathematical methods to real-world challenges and gaining hands-on experience that can lead to a full-time offer. The program emphasizes rigorous quantitative analysis, collaboration across teams, and development of scalable models and algorithms for capital and risk management across asset

Qualifications

• Enrolled in a PhD program, graduating Sep 2026–Mar 2028.
• Proficiency in Python and/or C++.
• Strong modeling, analytical and quantitative skills.
• Excellent communication for presenting complex concepts.
• Interest in banking analytics, markets, and quantitative research.
• Thrives in a fast-paced, collaborative environment.

Responsibilities

• Analyze data to identify patterns and trends.
• Back testing of strategies and model evaluation.
• Maintain and enhance risk/treasury software/tools.
• Assess models for soundness, risk, and improvements.
• Propose solutions to complex quantitative problems.
• Collaborate with internal teams to advance risk and treasury services.
• Develop, validate and enhance mathematical models and algorithms.
• Optimize financial solutions across asset classes.

Skills

Python

C++

Modeling

Analytical skills

Communication

Banking analytics

Teamwork

Education

PhD in mathematics/statistics/CS or related

Tools

R

MATLAB

SQL

Job description

JPMorgan Chase & Co. in London invites applications for the 2027 Quantitative Research - Risk and Treasury Off-Cycle Associate program.

You will work with senior quants on risk and treasury modeling, applying mathematical methods to real-world challenges and gaining hands-on experience that can lead to a full-time offer. The program emphasizes rigorous quantitative analysis, collaboration across teams, and development of scalable models and algorithms for capital and risk management across asset