RiskSpan · 4 months ago
Lead Mortgage Credit Modeler
Hybrid 3x/Week - Rosslyn-Arlington, Virginia
Full-time
Hybrid
Senior Level, Lead/Staff
7+ years expRiskSpan is a leading source of analytics, modeling, data, and risk management solutions for the Consumer and Institutional Finance industries. We are seeking a quantitative modeler with expertise in mortgage credit risk to design and implement advanced statistical and econometric models focusing on loan-level performance modeling and structured mortgage asset valuation.
AnalyticsData VisualizationFinancial ServicesRisk ManagementService Industry
Responsibilities
Develop and enhance loan-level mortgage credit risk models (transition matrices, hazard models, competing risks, survival analysis)
Implement econometric and machine learning approaches for prepayment, default, and severity modeling
Conduct back-testing, out-of-sample validation, and sensitivity analysis to assess model robustness
Analyze large-scale loan-level datasets (e.g., GSE loan-level, CoreLogic, Intex, private-label RMBS)
Build and document models in Python/R/C++, ensuring reproducibility and version control
Partner with structured finance and risk teams to integrate models into pricing, stress testing, and risk management frameworks
Research macroeconomic drivers of mortgage performance and their incorporation into stochastic scenario design
Author technical model documentation and research notes for internal stakeholders, model risk management, and regulators
Qualification
Required
Master's or Ph.D. in Quantitative Finance, Statistics, Econometrics, Applied Mathematics, or related quantitative discipline
7+ years of direct experience in mortgage credit risk modeling or structured finance analytics
Advanced skills in statistical modeling: survival analysis, proportional hazard models, logistic regression, generalized linear models, panel data econometrics
Strong programming expertise in Python (pandas, NumPy, scikit-learn, statsmodels) or R
Proficiency in handling big data (SQL, Spark, Snowflake and cloud-based data environments)
Deep knowledge of mortgage credit risk dynamics, housing market fundamentals, and securitization structures
Preferred
Experience with Hierarchical models, and Monte Carlo simulation
Knowledge of machine learning algorithms (e.g., gradient boosting, random forests, neural nets) applied to credit modeling
Familiarity with stress testing frameworks and regulatory model governance needs
Background in RMBS cash flow modeling and structured product analytics
Company
RiskSpan
RiskSpan Provides Risk Advisory, Managed Analytics And Technology Solutions.
51-200 employees
H1B Sponsorship
RiskSpan has a track record of offering H1B sponsorships. Please note that this does not
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2025 (15)
2024 (11)
2023 (11)
2022 (16)
2021 (19)
2020 (17)
Funding
Current Stage
Growth StageLeadership Team
Bernadette Kogler
Chief Executive Officer
Suhrud Dagli
Co-Founder
Recent News
2025-11-19
2025-10-18
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