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Quantitative Desk Strategist - Fixed Income - Associate

Morgan Stanley · New York

Full-time Posted 3 days ago

About this role

We are looking for a Quantitative Desk Strategist who combines strong quantitative modeling skills, fixed income derivatives knowledge, and hands-on software development experience. This role sits within the Strats organization and works closely with the trading desk. The focus is on developing analytics for complex fixed income products and building real-time risk systems that support daily trading decisions

It is a hands-on role that requires close collaboration with traders and strategists to solve practical trading problems. The ideal candidate can understand market risk, derivative pricing, and trading workflows, then translate those needs into practical models, scalable system design, and production-quality code. This role requires someone comfortable working across models, data, infrastructure, and user workflows, while keeping the desk’s real-time needs front and center

The ideal candidate can communicate clearly with both technical and non-technical audiences. You will questions such as: * How should we model, price, and risk-manage products such as Total Return Swaps, Tender Option Bond Trusts, bond options, interest rate swaps, and rates forwards? * How can we measure and explain risk across positions, products, curves, scenarios, as market moves in real time? * How do we build systems that are reliable, fast, and intuitive enough for traders to use during the trading day? * How can complex derivative analytics be turned into tools that improve trading decisions? * How do we design systems that are scalable, maintainable, and resilient under market pressure? ## ## Responsibilities * Develop quantitative models and analytics for pricing, risk, inventory, market impact, and trading performance. * Build reliable tools and workflows used directly by traders and strategists

* Analyze large, noisy, real-time datasets to identify patterns, risks, and opportunities. * Explain model results, assumptions, limitations, and tra

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