Senior Quantitative Analyst - Interest Rate Modeling & Risk Analytics

Bloomberg

New York (NY)

On-site

USD 100,000 - 140,000

Full time

14 days+

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Job summary

A leading financial data and technology company seeks an innovative quantitative research analyst to enhance valuation tools for US mortgage-backed securities. Ideal candidates will have over 4 years of experience in term structure modeling, strong analytical skills, and proficiency in SAS and Excel. This role involves collaboration with teams to develop analytical reports and models, making a significant impact in the financial markets.

Qualifications

  • 4+ years of experience in term structure modeling and risk management within the US Agency MBS Sector.
  • Experience with large datasets and conducting regression analysis.
  • Excellent verbal and written communication skills.

Responsibilities

  • Collaborate to enhance Bloomberg’s RFR market model for US mortgage-backed securities.
  • Develop tools for return attribution and risk management.
  • Create reports to track model performance and market risk.

Skills

Quantitative analysis
Regression analysis
Problem-solving
Data management
Communication skills

Education

BA/BS in Mathematics, Statistics, Economics or other quantitative field

Tools

SAS
Excel
Linux

Job description

Overview

The Bloomberg Structured Products team is responsible for all data, cash flows and analytics for the two million plus bonds that comprise the structured products universe. We own some of Bloomberg’s largest databases, highest hit services, most comprehensive cash flow model libraries, and most complex analytic tools and valuation screens. Our products support Bloomberg’s industry leading fixed income indices, security valuation services, portfolio management and trading platforms, as well as the daily workflow of countless traders, portfolio managers and research analysts.

Who we are

The Bloomberg Structured Products Quantitative Research Team

We are an enthusiastic, talented team of quants who work side by side with product managers, engineers, and sales to create high impact valuation, surveillance and risk management tools for both internal and external clients.

Our teams develop models that forecast cash flows for a variety of Agency, Non-Agency and ABS securities, produce valuation metrics used to determine relative value, and develop risk analytics used to quantify market risk for hedging and return attribution.

We strive to create best-in-class prepayment/credit models for the US Agency MBS/CMBS, US Residential Non-Agency, Credit Risk Transfer (CRT), Mortgage Insurance, HELOC/HEL, Auto ABS and Japanese MBS markets. We also develop the home price and interest rate models that help power our prepayment and credit models. Our models are developed in conjunction with a comprehensive suite of daily analytics reports, model surveillance reports, whitepapers, specified pool cohorts, and valuation tools.

We aim to provide timely model updates that incorporate the latest prepayment and credit data, stay in sync with evolving market developments and expand model coverage for new product types, while allowing clients the ability to fully customize their user experience with a comprehensive and intuitive set of model overrides.

We strive to continually improve our valuation and surveillance platform by maintaining an ongoing, open dialogue with the entire community of traders, portfolio managers, regulators, research analysts and mortgage agencies that incorporate our models into their daily workflow as well as internal partners such as Index/PORT, BVAL, MARS, NEWS and BI.

Our current Agency MBS projects include the development of a loan-level agency prepayment model and a new prepayment model for the GNMA project loan sector.

Our current residential credit projects include the development of a new prepay/credit model for securities backed by home equity lines of credit (HELOC) and home equity loans (HEL), and expanding multipath OAS coverage for existing sectors through BTM model service enhancements.

Other projects include updates to our mortgage rate models and the development of a new home price model.

Who you are

An innovative quantitative research analyst with a strong interest in financial markets. Someone who cares about the impact of their work and enjoys working with large datasets, conducting regression analysis, building analytic valuation tools, and supporting our clients. You enjoy collaborating and working closely with other people. You’re a problem solver, eager to learn, and have a strong interest in the structured products domain.

As part of this team, we\'ll trust you to
  • Work collaboratively with team members to manage and enhance the implementation of Bloomberg’s RFR market model for use in valuing US mortgage-backed securities
  • Work collaboratively with team members to develop and release tools for conducting return attribution, total/excess return analysis, interest rate/volatility scenario analysis, per path OAS analysis, and risk measurement/risk management of US mortgage-backed securities
  • Create analytical tools and reports that help clients track model performance, quantify market risk, and assess relative value
  • Contribute to whitepapers, published reports, and webinars
  • Help the team evolve and operate on a day-to-day basis
Qualifications
  • Strong quantitative experience within the US Agency MBS Sector with a focus on term structure modeling, PnL tracking, and risk management
  • 4+ years of professional experience building and maintaining term structure models used to value mortgage-backed securities
  • Strong quantitative, analytical and problem solving skills
  • Experience working with large data sets and conducting regression analysis
  • Proficiency in SAS or equivalent, Excel, Linux/windows environments
  • Excellent verbal and written communication and interpersonal skills
  • BA/BS in Mathematics, Statistics, Economics, or other quantitative field
We\'d love to see
  • MS or PhD in Mathematics, Statistics, Economics, or other quantitative field
  • A passion for financial markets
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