Home Loans Loss Forecasting Analytics, Senior Data Scientist

About This Role

Key ResponsibilitiesAI-extracted

• 1
  Develops quantitative and machine learning models to forecast losses across mortgage and home equity portfolios.
• 2
  Builds and maintains CECL, loss forecasting, and portfolio performance models with a focus on delinquency roll rates and default probability.
• 3
  Defines and maintains portfolio performance KPIs across credit, profitability, and risk, including delinquency rates and loss rates.
• 4
  Performs cohort, vintage, and segmentation analysis by credit score, LTV/CLTV, DTI, and other factors.
• 5
  Builds roll-rate models, delinquency migration analytics, cure models, default models, recovery models, and loss severity frameworks for secured lending portfolios.
• 6
  Supports collections, loss mitigation, and default strategy analytics, including segmentation and treatment strategy measurement.

RequirementsAI-extracted

• 5+ years of experience in data science, statistical modeling, credit risk analytics, or a related quantitative role.
• Master's or PhD in Statistics, Mathematics, Economics, Engineering, Computer Science, Operations Research, Finance, or another quantitative field.
• Strong proficiency in Python and SQL, with experience building repeatable analytical pipelines and automated reporting.
• Experience with data visualization and dashboarding tools such as Tableau, Looker, Power BI, or similar platforms.
• Demonstrated experience with credit risk modeling, loss forecasting, CECL, roll-rate modeling, delinquency/default modeling, recovery modeling, or portfolio performance analytics.
• Hands-on experience with mortgage or secured lending data, including first liens, jumbo loans, HELOCs, closed-end seconds, or other collateral-backed products.

Perks & BenefitsAI-extracted