Principal Modeler Mortgage Loan Performance

RiskSpan; Arlington (VA); On-site; USD 180,000 - 200,000; Full time

Job summary

RiskSpan is seeking a seasoned quantitative modeler to own the development and enhancement of loan-level mortgage prepayment and credit performance models. You will set technical standards for mortgage modeling, partnering with structured finance and risk teams on the Edge platform.

This principal-level role requires deep domain expertise and leadership. You will lead econometric and ML approaches, build modeling pipelines in Python/R/C++ on Linux, and mentor junior modelers while integrating

Qualifications

• Advanced degree required in a quantitative field with a strong focus on mortgage prepayment or credit modeling.
• Extensive hands-on experience with loan-level mortgage data and RMBS modeling is essential.
• Demonstrated ability to lead long-term research projects and deploy models into production.

Responsibilities

• Own development and enhancement of loan-level prepayment and credit performance models for agency and non-agency collateral.
• Lead econometric and ML approaches for prepayment and credit behavior modelling, including survival analysis and gradient boosting.
• Build end-to-end modeling pipelines in Python, R, and/or C++ on Linux, from data ingestion to deployment.
• Back-test models, run sensitivity analyses across rate environments, vintages, and borrower cohorts.
• Research macroeconomic drivers and incorporate them into stochastic scenario design; apply Monte Carlo simulations for asset valuation and hedging.
• Document modeling work and mentor junior modelers to establish technical standards.

Skills

Survival analysis

Proportional hazards

Gradient boosting

OAS modelling

Monte Carlo simulation

Education

Master's or PhD in Quantitative Finance / Statistics / Econometrics / Applied Math

Tools

Python

R

C++

SQL

Job description

We build the analytics and data infrastructure that mortgage and structured finance professionals rely on to understand risk, run models, and make decisions with confidence. Our platform, Edge, serves portfolio managers, risk teams, and quantitative analysts at some of the most sophisticated financial institutions in the market. We're growing and we need the operational foundation to match.

TL;DR

We're looking for a seasoned quantitative modeler to own the development and enhancement of loan-level mortgage prepayment and credit performance models. You'll bring deep domain expertise, set the technical standard for how we approach mortgage modeling, and partner directly with our structured finance and risk teams. This is a principal-level role for someone who has done this work before and is ready to own it.

What you'll do

Build

Own and advance loan-level prepayment models across agency and non-agency collateral - S-curves, refinance incentive functions, seasoning ramps, burnout, seasonality, turnover etc

Lead econometric and ML approaches for prepayment and credit behavior modeling, including survival analysis, competing risks, and gradient boosting; extend to default and severity modeling.

Own credit risk modeling efforts including delinquency transitions, default, and loss given default

Build full modeling pipelines in Python (pandas, NumPy, scikit-learn, statsmodels), R, and/or C++ on Linux - from data ingestion through validation and deployment

Validate and Research

Back-test models and run sensitivity analysis across rate environments, vintages, and borrower cohorts

Analyze GSE, GNMA, and private-label RMBS loan performance data using SQL and Snowflake to identify behavioral drivers and shifts

Research macroeconomic and borrower-level prepayment drivers - mortgage rate spreads, home price appreciation, credit availability - and incorporate them into stochastic scenario design

Apply Monte Carlo simulation, OAS frameworks, and interest rate models to support structured mortgage asset valuation and hedging

Integrate and document

Partner with structured finance and risk teams to integrate models into pricing, OAS analysis, hedging, and risk management frameworks

Set documentation standards and author technical model documentation and research notes for internal stakeholders, model risk management, and regulators

Mentor and provide technical guidance to junior modelers on the team

Who you are

Master's or Ph.D. in Quantitative Finance, Statistics, Econometrics, Applied Math, Physics, or a related field

7-10+ years of hands-on mortgage prepayment or credit performance modeling experience

Deep expertise in agency and non-agency MBS markets, TBA pricing, prepayment benchmarks, and RMBS cash flow modeling

Strong programming skills in Python, R, C++ on Unix/Linux, and SQL

Experienced with statistical modeling - survival analysis, proportional hazard models, logistic regression, GLMs, panel data econometrics

Proficient in analyzing large datasets using SQL, Snowflake, and cloud-based data environments

Proven ability to set technical direction and drive long-term research projects through to deployment

Exposure to Monte Carlo simulation, OAS, stress testing frameworks, or model governance a plus

What we offer

Base salary range of $180,000 - $200,000

Exact compensation depends on experience, skills, location, and market data

Benefits package including paid time off, 401k, and medical, dental, and vision insurance options

Meaningful work in a technically complex, high-stakes industry, building models that practitioners rely on

A collaborative team that operates at the leading edge of mortgage and structured finance modeling