Quantitative Trading & Research – Credit Portfolio – Quantitative Developer – Associate or Vice President

Quantitative Trading & Research (QTR) is an expert quantitative modelling group in J.P. Morgan. As a global team, QTR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls. Job summary: We are seeking an experienced Associate or Vice President to join our Quantitative Trading & Research (QTR) team in London. Our mission is to develop analytics for the Credit Portfolio Group (CPG) which sits within the Markets division of the Commercial and Investment Bank (CIB). About the Credit Portfolio Group (CPG): CPG is responsible for managing the firm’s credit and funding valuation adjustments (CVA and FVA), which are critical to the bank’s risk management and pricing strategies. The group develops and maintains a large-scale Monte-Carlo engine in order to effectively manage these adjustments. Advanced numerical and computational techniques are used to achieve this including the use of Adjoint Analytic Differentiation (AAD). Job Responsibilities: As an Associate or a Vice President in the Quantitative Trading & Research – Credit Portfolio team, you will contribute to our agenda to transform the investment bank into a data-driven business, promoting change through state-of-the-art AI and machine learning techniques. This is a hands-on, implementation-focused role, and we are looking for someone with proven experience designing and building scalable, efficient, production-grade solutions. As such, a strong quantitative background is not a key requirement for this role. Design, develop, and enhance our large-scale Monte Carlo simulation engine used for computing Credit Valuation Adjustment (CVA) and Funding Valuation Adjustment (FVA) across the firm's derivatives portfolio. Implement advanced numerical techniques to further improve computational efficiency and accuracy of risk sensitivities. Contribute to the firm's strategic agenda of transforming the investment bank into a data-driven business through the development of scalable, high-performance analytical tools and infrastructure. Collaborate with technology teams, ensuring robustness, performance, and maintainability of code in a large-scale production environment. Partner closely with traders, marketers, and risk managers across all products and regions to deliver analytical solutions that meet business needs. Drive best practices in quantitative research, software development, and analytical rigor across the team. Required qualifications, capabilities, and skills: Hands-on experience building and shipping software in an engineering or quantitative role, with a track record of taking solutions from idea to production Degree in a quantitative or engineering field such as Computer Science, Engineering, Mathematics, or Physics Demonstrate strong, practical programming skills, particularly in Python, with hands-on experience developing large-scale, production-grade systems and a willingness to learn and apply best coding practices A genuine problem solver who has personally designed and implemented working solutions to real problems in their role Ability to contribute to technical projects from conception through delivery, including architecture decisions and stakeholder management Support robust system and solution architecture, contributing to rigorous testing, verification, and adherence to best practices in design and implementation Solid software engineering, algorithm design, and development skills with a commitment to robust testing, verification, and code quality standards Strong communication and influencing skills, both verbal and written, with the ability to engage partners and stakeholders on complex and technical topics with clarity Preferred qualifications, capabilities, and skills: Advanced degree (e.g. PhD) in Engineering, Mathematics, Physics or Computer Science Markets experience and familiarity with general trading concepts and terminology Knowledge of options pricing theory, trading algorithms or financial regulations Experience with robust testing and verification practices