Loans Loss Forecasting Analytics, Senior Data Scientist

Overview

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Senior Data Scientist – Home Lending Risk Analytics. Focus on loss forecasting and portfolio performance monitoring for first mortgages, jumbo loans, closed‑end seconds, and HELOCs, with a strong emphasis on delinquency, default, cure, severity, recovery, and portfolio profitability. Build models, dashboards, and analytical frameworks that help the Secured Lending organization understand credit performance across the full residential lending lifecycle, from origination and portfolio monitoring through delinquency, default resolution, loss mitigation, and recovery.

Work closely with Credit Decision Science, Credit Risk, Finance, Capital Markets, Servicing, Collections, Loss Mitigation, Model Risk, and Data Engineering to support data‑driven decision‑making across Home Lending.

• Develop quantitative and machine learning models to forecast losses across mortgage and home equity portfolios, including first lien, jumbo, HELOC, and closed‑end second‑lien products.
• Build and maintain CECL, loss forecasting, and portfolio performance models with a focus on delinquency roll rates, default probability, cure behavior, loss severity, recovery timing, prepayment behavior, and charge‑off outcomes.
• Define and maintain portfolio performance KPIs across credit, profitability, and risk, including delinquency rates, roll rates, cure rates, loss rates, severity, prepayment speeds, early payment defaults, repurchase risk, defect rates, and recovery performance.
• Perform cohort, vintage, and segmentation analysis by credit score, LTV/CLTV, DTI, lien position, documentation type, occupancy, channel, state/metro, property type, investor, and product type.
• Analyze borrower behavior and identify key risk drivers across stages of credit performance, including current status, early delinquency, late‑stage delinquency, default, liquidation, foreclosure, recovery, and redefault.
• Build roll‑rate models, delinquency migration analytics, cure models, default models, recovery models, and loss severity frameworks for secured lending portfolios.
• Support collections, loss mitigation, and default strategy analytics, including segmentation, treatment strategy measurement, liquidation waterfalls, cure versus liquidation outcomes, modification performance, and recovery optimization.
• Develop analytics that evaluate resolution pathways, including cure, modification, repayment plan, foreclosure, liquidation, REO, charge‑off, and expected recovery cash flows.
• Build and maintain executive dashboards and automated reporting that clearly explain what changed, why it changed, and what actions should be considered next.
• Partner with Data Engineering to define data requirements, improve data quality, create new data sources, and build summarized analytical tables that support scalable reporting, monitoring, and modeling.
• Aggregate and synthesize datasets from multiple environments, including origination data, servicing systems, collections data, collateral data, bureau data, investor/product data, and external housing market data such as HPI.
• Perform sensitivity, scenario, and stress analysis tied to home price movements, interest rates, unemployment, credit mix, prepayment behavior, and broader economic conditions.
• Monitor model and portfolio performance through back‑testing, forecast‑to‑actual tracking, population stability, segmentation diagnostics, drift monitoring, and periodic recalibration.
• Prepare clear, audit‑ready documentation for models, assumptions, dashboards, data sources, business logic, reporting…