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The Global Fixed Income, Currency and Commodities team (GFICC) at J.P. Morgan Asset Management is one of the world's deepest and best-resourced fixed income managers, with expertise across all major fixed income sectors, including niche markets. Every investment decision in our fixed income solutions is underpinned by the proprietary research of a globally integrated team of sector specialists. GFICC manages a broad range of strategies — including High Yield, Systematic Fixed Income, Short Duration, Core/Core Plus, Investment Grade Credit, Emerging Market Debt, Securitized, and Tax-Aware strategies — through funds and separate accounts across the globe.

As an Analyst or Associate Investment Specialist within GFICC, you will support the High Yield and Systematic investment businesses. This is a dual-mandate role: you will contribute to client-facing investment specialist responsibilities while serving as a technology and innovation resource for the broader GFICC team. You will work at the intersection of fixed income markets and cutting‑edge technology, applying tools including artificial intelligence, machine learning, and advanced data analytics to drive efficiencies, improve workflows, and generate insight across the platform. We are looking for a naturally curious problem‑solver who brings both investment market awareness and genuine technical depth, and who thrives in a fast‑paced, intellectually demanding environment.

• Partner with senior Investment Specialists, Portfolio Managers, and Client Advisors on new business development and client retention across High Yield and Systematic strategies.
• Contribute to the production of pitch materials, RFPs, and due diligence responses.
• Prepare fund and strategy presentations, performance commentaries, and other client communications.
• Participate in client meetings and internal forums to support articulation of market views, portfolio positioning, and performance attribution.
• Assist in addressing client inquiries related to current market events and portfolio dynamics.
• Support training of the J.P. Morgan Asset Management sales force on fixed income and quantitative topics.

• Proactively identify opportunities to leverage AI, large language models, automation, and advanced data tools to streamline workflows across GFICC.
• Design and build scalable solutions — using Python, APIs, and relevant AI frameworks — to reduce manual effort in performance reporting, market commentary generation, data aggregation, and presentation production.
• Stay current on emerging technologies and evaluate their practical applicability within an asset management context.
• Collaborate with technology, data, and investment teams across GFICC to translate business problems into well‑engineered, repeatable solutions.
• Bring a rigorous, solutions‑oriented mindset to every challenge, with a focus on creating durable efficiencies across the platform.

• Bachelor's degree.
• Up to 3+ years of relevant work experience; exceptional recent graduates with demonstrated technical capability will be considered.
• Strong proficiency in Python — comfortable writing clean, functional code and applying it to real analytical problems.
• Working knowledge of global fixed income markets, with familiarity with High Yield or Systematic strategies in particular.
• Genuine intellectual curiosity and a structured, hypothesis‑driven approach to problem‑solving.
• Strong written and verbal communication skills, including the ability to convey complex quantitative or technical concepts to non‑technical audiences.
• Familiarity with Bloomberg and advanced proficiency in Excel and PowerPoint.
• Ability to manage multiple workstreams simultaneously, meet tight deadlines, and maintain rigorous attention to detail.

• Prior exposure to machine learning frameworks, large language model APIs, or workflow automation tools.
• Experience with data visualization platforms, cloud computing environments, or financial data infrastructure.
• Degree in Computer Science, Engineering, Mathematics, Statistics, Finance, Economics, or a related quantitative or technical discipline
• CFA candidacy or demonstrated progress toward the designation.
• Prior internship or project experience within asset management, quantitative research, or financial technology.