RMBS Quantitative Researcher - Prepayment Modeling (VP/Assoc.)
A Tier 1 US Investment Bank is seeking a highly skilled quantitative researcher to join our structured products analytics team, focusing on Agency OR Non-Agency RMBS prepayment modeling. This role is critical for developing advanced borrower behavior models that drive valuation, risk management, and trading strategies. The ideal candidate will have strong technical expertise, deep knowledge of mortgage analytics, and exceptional programming skills.
- Prepayment Model Development:
- Design, implement, and maintain sophisticated prepayment models for Agency OR Non-Agency RMBS, incorporating refinancing incentives, burnout effects, housing market trends, and macroeconomic drivers.
- Integrate prepayment models into pricing, risk, and hedging platforms for structured products.
- Default Modeling:
- Develop complementary models for default and loss forecasting to ensure comprehensive risk assessment.
- Combine prepayment and credit models for scenario analysis and stress testing.
- Data Analysis & Calibration:
- Conduct rigorous analysis of historical loan-level and pool-level performance data.
- Apply econometric techniques, hazard rate modeling, survival analysis, and logistic regression for model calibration.
- Infrastructure & Implementation:
- Build scalable platforms for large-scale data processing and model deployment.
- Optimize computational efficiency for production environments using advanced numerical methods.
- Governance & Documentation:
- Prepare detailed documentation for all models in compliance with internal governance and regulatory standards.
- Support model validation and review processes.
- Collaboration & Training:
- Partner with trading desks, risk teams, and technology groups to ensure proper model usage.
- Provide training and guidance to internal stakeholders on model functionality and interpretation.
- PhD highly preferred in a quantitative discipline (Mathematics, Statistics, Economics, Computer Science, Engineering, or related field).
- Strong programming skills in C++ and Python, with experience building production-level models and analytical tools.
- Expertise in prepayment modeling for Agency OR Non-Agency RMBS, including borrower behavior analysis and econometric techniques.
- Proficiency in hazard rate models, survival analysis, and logistic regression.
- Experience with Monte Carlo simulations and factor modeling (e.g., PCA).
- Skilled in data manipulation and statistical analysis using Python libraries (NumPy, Pandas, StatsModels).
- Familiarity with Linux environments and shell scripting for automation.
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