Quantitative Research Asset-Backed Securities - Associate

Description

This is an exciting opportunity to use Machine Learning and other techniques to design pre-trade and risk analytics in the Asset-Backed Securities businesses.

Job summary

As an Associate in the Quantitative Research Structured Product Group (SPG) Asset-Backed Securities (ABS) team based in New York, you will engage in the design and implementation of risk and pre-trade analytics for these products. We are broadly tasked with developing and maintaining models for valuation, risk, P&L calculations, as well as creating quoting and market-making algorithms and analytical tools. The team also supports Commercial Mortgage-Backed Securities (CMBS), so there will be further opportunities for collaboration. We utilize Machine Learning and other statistical techniques in developing these models, and then document them to satisfy high internal and regulatory standards.

Job responsibilities

Develop, maintain, and enhance models for the SPG ABS businesses

Document models to pass strict regulatory and in-house standards

Develop and model performance tracking and regulatory analysis

Work closely with technology teams on integration of models in applications

Support trading activities by explaining model and algorithm behavior

Required qualifications, capabilities and skills

MS or PhD in finance, mathematics, computer/data science, physics, or other quantitative field

Strong financial modeling skills including Machine Learning

Strong software design skills and ability to code models in Python and C++

Excellent communication and writing skills

Ability to work in a high-pressure environment and a good team worker

Preferred qualifications, capabilities and skills

Structured product (ABS/CMBS) experience is a plus