Posted Aug 28, 2017 - Requisition No. 61253
Structured Products securitize residential and commercial mortgage loans, as well as consumer debt such as auto, student, and credit card loans, and represent a significant part of the global financial markets. As the Fed reduces its MBS holdings and GSEs, like Freddie Mac, increasingly employ innovative products to transfer credit risk to investors, trading activities are growing and so are demands for advanced risk analytics. The Bloomberg Structured Products Risk team has long been on the frontline, providing indispensable predictive models and risk analytics that allow investors to effectively value the optionality (inherent from underlying loan prepayments and defaults) in Structured Product securitizations, in both the US and International markets.
You will be a part of a team that applies quantitative models to analytical and algorithmic problems. We analyze large volumes of loan data to discover the correlations between market dynamics and borrower prepayment and default behaviors. We employ interest rate term structure models, home price appreciation projections, loan transition simulations, and Monte Carlo forward interest rate paths to perform option adjusted spread (OAS) calculations. We develop algorithms using a combination of C++ and Python, leveraging large scale distributed computing architectures. You will make significant contributions to our product, while learning the complexities of the Structured Products domain. Finally, you'll gain market expertise through your collaboration with business managers, financial engineers and quantitative researchers.