Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
This Associate role is part of the Emerging Markets Debt (EMD) platform within JPMorganChase, supporting portfolio managers across Local, External, Corporate, and Blended strategies. The primary mandate is to enhance investment-team productivity through disciplined automation and to strengthen portfolio construction and risk analytics. The role involves hands-on quantitative work combined with practical tooling, including compliant use and integration of AI/LLM-enabled workflows. Reporting to the Head of EMD / Senior Portfolio Manager, you will join a technically strong team focused on building scalable analytics, portfolio construction tools and agents, and automated reporting that improve decision-making and execution efficiency across the franchise.

You will design and deploy automated workflows for recurring materials, identify process bottlenecks, and implement durable fixes using modern tooling, including LLM-based assistants in line with firmwide data governance standards. You will develop and enhance portfolio construction and optimization capabilities, including risk budgeting, factor exposure analysis, and scenario modelling. Responsibilities also include building and maintaining models, dashboards, and datasets for signals, valuation, and risk monitoring, with scope to support systematic and rules-based strategy development. Additionally, you will provide day-to-day investment support to portfolio managers and research analysts, including ad hoc analysis, trade idea evaluation, implementation support, and contributions to performance attribution and risk analytics.

Experience
2-4 years of relevant experience in asset management, quantitative finance, or a closely related field. Strong programming capability in Python is required. Experience with fixed income products is necessary, with emerging markets experience preferred. Familiarity with AI/LLM-assisted tools and integration is expected.

About you
Strong communication skills and high operational attention to detail. You are technically proficient, proactive, and able to work collaboratively within a team environment. You have a passion for quantitative finance and automation, with a commitment to improving investment processes and outcomes.

Qualifications
A degree in Economics, Finance, Applied Mathematics, Computer Science, or a related quantitative discipline is preferred. An advanced degree and/or progress toward the CFA designation is viewed positively. Additional advantages include familiarity with portfolio construction and attribution frameworks, data visualization tools such as Tableau or Power BI, exposure to systematic strategy or indexing/ETF construction, and understanding of order management and trade execution workflows.