below marketmost similar roles pay hereabove market
This role pays more than
97%
of similar roles. Most pay
$147,950–$212,125
— the blue band above.
At the midpoint, this role pays about
$285k
versus about
$180k
for comparable roles.
Based on 240 similar postings.
Employer
About Wells Fargo
Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services
Wells Fargo currently has
37 open roles
on FindRole.
Listed pay typically runs
$139,000–$239,000
across 16 roles with salary data.
The Senior Lead Securities Quantitative Analytics Specialist leads quantitative modeling for residential mortgage and non-agency RMBS. This role involves leading the research, development, and enhancement of loan- and pool-level models for prepayment, delinquency, default, cure, liquidation, recovery, and loss severity. The specialist will build model-ready datasets, conduct empirical research on borrower behavior, and translate collateral projections into RMBS cash flows, valuations, and risk measures. Key responsibilities include performing back-testing, sensitivity analysis, and providing technical leadership to the team. Required skills include expertise in statistics, econometrics, financial mathematics, and Monte Carlo simulations. The role utilizes Python, SQL, and platforms like 1010data, McDash, Intex, and Loan Performance. The work focuses on capturing refinancing incentives, credit migration, and housing conditions to support pricing, portfolio management, and risk management.
Lead the research, design, development, calibration, and enhancement of loan- and pool-level mortgage models.
Conduct empirical research on borrower behavior and mortgage credit performance using large-scale loan-level and macroeconomic data.
Build and maintain model-ready datasets while evaluating data quality, coverage, and historical performance.
Apply statistical, econometric, and machine learning techniques to capture refinancing incentives and credit migration.
Translate collateral-level projections into RMBS cash flows, valuations, risk measures, and stress-testing results.
Perform model back-testing, benchmarking, sensitivity analysis, and ongoing performance monitoring to identify limitations.
Develop clear model documentation covering methodology, assumptions, estimation, and intended use for regulatory and audit review.
Provide technical leadership by reviewing quantitative work and mentoring less experienced team members.
What we're looking for
7+ years of Securities Quantitative Analytics experience, or equivalent demonstrated through work experience, training, military experience, or education.
7+ years of experience developing mortgage securities, prepayment, default, credit, or other residential mortgage behavioral models (preferred).
Master’s degree or Ph.D. in mathematics, statistics, physics, engineering, computer science, quantitative finance, economics, or another highly quantitative discipline (preferred).
Strong understanding of residential mortgage products, securitization structures, waterfall mechanics, mortgage cash flows, pricing, valuation, and OAS analytics (preferred).
Demonstrated experience working with large-scale mortgage datasets and platforms such as 1010data, eMBS, Loan Performance, CoreLogic, McDash, and Intex (preferred).
Strong knowledge of statistics, econometrics, financial mathematics, Monte Carlo simulation, and mortgage analytics (preferred).
Advanced programming and data-analysis experience using Python and SQL; experience with C++ or VBA is a plus (preferred).
Experience developing, calibrating, back-testing, monitoring, and documenting quantitative models through the model development lifecycle (preferred).