Quantitative Model Analyst 4 – Mortgage Modeling
| Company | U.S. Bank |
|---|---|
| Location | Hopkins, MN, USA, St Charles, MO, USA, New York, NY, USA |
| Salary | $119765 – $140900 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s degree in a quantitative field, and eight or more years of relevant experience
- OR MA/MS in a quantitative field, and five or more years of related experience
- OR PhD in a quantitative field, and four or more years of related experience
- Has an advanced to expert understanding of applicable laws, regulations, financial services, and regulatory trends that affect the Mortgage business
- Has a strong statistical modeling background based on technical training or advanced education in a quantitative field
Responsibilities
- Lead and manage all phases of large complex model development, validation, or oversight projects from beginning to end
- Projects may include data aggregation, model design, model selection, testing, documentation, validation, implementation, and execution
- Responsible for training lower level and new staff
- May manage or supervise Quantitative Model staff as assigned
- Interacts directly with senior managers requiring expert level of presentation, relationship building and negotiation skills
- Exposure to regulatory agencies
Preferred Qualifications
- Advanced understanding of applicable laws, regulations, financial services, and regulatory trends that affect the mortgage business
- Knowledge of the Mortgage Industry, specifically pertaining to mortgage servicing rights (MSR) valuation, market risk hedging, and current coupon/primary mortgage rate generation
- Experience modeling or analyzing mortgage prepayments and delinquencies
- Advanced statistical modeling background based on technical training or advanced education in a quantitative field
- Advanced knowledge of various regression techniques (linear, logistic), parametric and non-parametric algorithms, times series techniques (ARIMA, GARCH), and other statistical models, various model validation tests/methodologies, using SAS, R, or similar statistical package
- Advanced data compilation, programming skills and qualitative analysis skills such as Python, VBA, and C++
- Advanced knowledgeable of quantitative and qualitative risk factors (duration, convexity), industry risks, competition risks, and risk management approaches
- Demonstrated independence, teamwork, and leadership skills
- Strong project management skills
- Excellent written and verbal communication skills