Quantitative Analyst - Cross Asset Financing

UBS•New York, NY

3d•$225,000 - $242,500

About The Position

The Quantitative Analyst will research, develop, and enhance valuation and risk-management models and tools supporting Cross Asset Financing businesses, including Structured Financing and Fund Financing. The role applies quantitative methods to model complex fund structures in bespoke Fund Financing facilities and uses advanced statistical techniques to develop prepayment and default models for securitized products. The analyst partners with other Quantitative Analytics teams to create automated, scalable cross-asset solutions for Trading, Structuring, and Sales, and collaborates with Trading, Structuring, Risk, and Control functions on statistical analysis, valuation and risk methodologies, and business decision-making. The position is part of UBS's Credit Quantitative Analytics team, a Front Office group that develops quantitative models, methodologies, and technology for pricing and risk management across Credit businesses. Its models and infrastructure support client quoting, trading-position risk management, and the marking of the firm's books and records. The team works closely with Trading, Structuring, IT, control functions, and other Quantitative Analytics teams.

Requirements

Strong academic background in a quantitative discipline such as Mathematics, Physics, Computational Finance, Engineering, or a related field.
At least 5 years of relevant work experience.
Proficiency in an object-oriented programming language such as C, C#, Java, or Python, with the ability to develop robust and scalable quantitative solutions.
Solid foundation in quantitative finance and derivatives pricing, with knowledge of modern numerical and/or machine-learning techniques.
Ability to identify and drive opportunities to apply AI and emerging technologies responsibly to enhance business outcomes and operational efficiency.
Strong stakeholder-management and influencing skills, and the ability to communicate complex ideas fluently and articulately.
Sound judgment when using AI, including validating outputs and aligning with policies, risk standards, and ethical-use requirements.

Nice To Haves

Master’s or PhD-level education in a quantitative discipline.
Knowledge of securitized products, fixed income analytics, and complex fund structures.

Responsibilities

Research, develop, and enhance valuation and risk-management models and tools for Cross Asset Financing businesses, including Structured Financing and Fund Financing.
Apply quantitative techniques to model complex fund structures in bespoke Fund Financing facilities.
Use advanced statistical techniques to develop prepayment and default models for securitized products.
Partner with other Quantitative Analytics teams to develop automated and scalable cross-asset solutions for Trading, Structuring, and Sales.
Collaborate with Trading, Structuring, Risk, and Control functions to perform statistical analysis, develop valuation and risk methodologies, and support business decision-making.