Senior Quantitative Analyst – Interest Rate Modeling & Risk Analytics

Details

The Bloomberg Structured Products team develops data, cash flow, valuation, surveillance, and risk analytics for more than two million structured product bonds. Its products support fixed income indices, security valuation services, portfolio management, trading platforms, and the workflows of traders, portfolio managers, and research analysts.

The Structured Products Quantitative Research Team works with product managers, engineers, and sales to create valuation, surveillance, and risk management tools for internal and external clients. The team develops models for Agency, Non-Agency, and ABS securities, including prepayment, credit, home price, and interest rate models.

Current projects include loan-level Agency MBS prepayment modeling, GNMA project loan prepayment modeling, HELOC and HEL prepayment and credit modeling, multipath OAS coverage, mortgage rate model updates, and a new home price model.

Responsibilities

• Collaborate with team members to manage and enhance Bloomberg’s RFR market model for valuing US mortgage-backed securities.
• Develop and release tools for return attribution, total and excess return analysis, interest rate and volatility scenario analysis, per-path OAS analysis, and risk measurement and 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 evolve and operate the team’s products and processes on a day-to-day basis.

Requirements

• Strong quantitative experience within the US Agency MBS sector, focused on term structure modeling, P&L tracking, and risk management.
• At least 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 datasets and conducting regression analysis.
• Proficiency in SAS or an equivalent tool, Excel, and Linux or Windows environments.
• Excellent verbal, written, and interpersonal communication skills.
• Bachelor’s degree in Mathematics, Statistics, Economics, or another quantitative field.

Preferred Qualifications

• Master’s or PhD in Mathematics, Statistics, Economics, or another quantitative field.
• Passion for financial markets.

Benefits

Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.