Emerging Markets Debt (EMD) – Quantitative Solutions & Portfolio Construction (Associate)
Executive Summary
This Associate role sits within the Emerging Markets Debt platform, supporting portfolio managers across Local, External, Corporate, and Blended strategies. The mandate is to improve investment-team productivity through disciplined automation and to strengthen portfolio construction and risk analytics. The role combines hands-on quantitative work with practical tooling, including compliant use and integration of AI/LLM-enabled workflows. Location is London, reporting to the Head of EMD / Senior Portfolio Manager (per provided role description).
Role Summary
Join the EMD investment team as a technically strong Associate focused on building scalable analytics, portfolio construction tools and agents, and automated reporting that improve decision-making and execution efficiency across the franchise.
Core Responsibilities
You will design and deploy automated workflows for recurring materials, identifying process bottlenecks and implementing 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. This includes building and maintaining models, dashboards, and datasets for signals, valuation, and risk monitoring, with scope to support systematic and rules-based strategy development.
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.
Required Qualifications
Candidates should bring 2–4 years of relevant experience in asset management, quantitative finance, or a closely related field, with strong programming capability in Python (required). Comfort using and integrating AI/LLM-assisted tools is needed, alongside solid communication skills and high operational attention to detail. Fixed income knowledge is required, with emerging markets experience preferred
Preferred Qualifications
A degree in Economics, Finance, Applied Mathematics, Computer Science, or a related quantitative discipline is preferred, with an advanced degree and/or progress toward the CFA viewed positively. Additional advantages include familiarity with portfolio construction and attribution frameworks, data visualization tools (for example Tableau or Power BI), exposure to systematic strategy or indexing/ETF construction, and understanding of order management and trade execution workflows (per provided role description).