Senior Quantitative Analyst - Term Structure Modeling

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, researchdriven group of quants and engineers building productiongrade 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 RFRbased (SOFR) market models, including curve construction, dynamics, and volatility representation across caplets, swaptions, and mortgage products Implement and support scenariobased analytics, including rate, curve, and volatility shocks, perpath simulations, and attribution analysis Contribute to the development of stochastic volatility frameworks and factorbased simulations (e.g., PCAdriven 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, productionready 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 mortgagebacked securities or structured products Strong experience with rates volatility modeling, scenario analysis, and simulationbased valuation methodologies Proficiency in Python (and/or equivalent quantitative programming languages) with experience working in largescale 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 SABRstyle volatility models, stochastic volatility frameworks, or factorbased curve simulations Background in US Agency MBS, mortgage modeling, prepayment analytics, or OASbased valuation Familiarity with Linuxbased research environments and production analytics platforms Passion for financial markets and a desire to work on models that directly impact realworld investment decisions