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Senior Quantitative Analyst - Term Structure Modeling
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Selby Jennings
New York, NY (In Person)
Full-Time
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Job Description
A leading global financial technology and analytics platform, fresh off a period of strong growth and continued investment in its fixed income analytics stack, is actively expanding its Structured Products Quantitative Research team in New York. This is an outstanding opportunity to work alongside a highly technical, research‑driven group of quants and engineers building production‑grade models and analytics used daily by institutional investors, traders, and portfolio managers across global fixed income markets. Responsibilities Design, develop, and maintain interest rate term structure and volatility models used for valuation, OAS analysis, and risk measurement of Agency MBS and structured products Enhance RFR‑based (SOFR) market models, including curve construction, dynamics, and volatility representation across caplets, swaptions, and mortgage products Implement and support scenario‑based analytics, including rate, curve, and volatility shocks, per‑path simulations, and attribution analysis Contribute to the development of stochastic volatility frameworks and factor‑based simulations (e.g., PCA‑driven curve dynamics) for pricing and hedging applications Build and maintain analytical tools, libraries, and pipelines that support cash flow forecasting, valuation metrics, and risk analytics Partner closely with researchers, engineers, and product stakeholders to translate quantitative models into robust, production‑ready software Requirements 4+ years of professional experience in quantitative research, interest rate modeling, or risk analytics within a production environment Deep expertise in interest rate term structure modeling, with direct application to mortgage‑backed securities or structured products Strong experience with rates volatility modeling, scenario analysis, and simulation‑based valuation methodologies Proficiency in Python (and/or equivalent quantitative programming languages) with experience working in large‑scale analytical codebases Demonstrated experience working with large datasets, regression analysis, and statistical modeling techniques Strong academic background with a BA/BS in Mathematics, Statistics, Economics, Financial Engineering, or a related quantitative discipline Excellent communication skills and a collaborative mindset Preferred Qualifications Advanced degree (MS or PhD) in a quantitative field Experience with SABR‑style volatility models, stochastic volatility frameworks, or factor‑based curve simulations Background in US Agency MBS, mortgage modeling, prepayment analytics, or OAS‑based valuation Familiarity with Linux‑based research environments and production analytics platforms Passion for financial markets and a desire to work on models that directly impact real‑world investment decisions