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.

What's in it for you:

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.

We'll trust you to:

• Collaborate with our quant and engineering teams to design and implement predictive models for projecting prepayment, default and forward rate assumptions
• Partner with product managers in understanding clients' risk management workflows to design and build software solutions that meet and exceed their expectations
• Proactively lead initiatives by driving requirement definitions, project estimations, sprint scheduling, risk mitigation and tactical deployment

You'll need to have:

• 3+ years of experience programming, preferably in C/C++ and Python
• A solid understanding of data structures, algorithms and object-oriented design- Strong communication, analytical and problem-solving skills
• Ability to write clear and well-documented code in a fast paced environment
• A Bachelor's degree in Computer Science, Math, Engineering, Finance or equivalent experience