Phoenix, AZ

• •Lead Model Validation Quality Assurance for enterprise risk and finance models across credit, liquidity, and capital planning portfolios.
• •Direct multi-disciplinary teams of quantitative analysts, data scientists, and engineers ensuring conceptual soundness, implementation accuracy, and performance monitoring.
• •Built automation pipelines in Python and SQL on AWS to streamline validation testing and report generation — cut cycle time by 30%.
• •Partner with IT and Enterprise Data Architecture to modernize model inventory and metadata tracking for regulatory compliance and audit readiness.
• •Developed AI/ML model explainability and fairness frameworks integrated with Power BI dashboards for executive oversight.
• •Mentor teams on validating emerging ML and generative AI models in marketing, fraud detection, and credit risk applications.

Tempe, AZ

• •Built predictive pricing and risk models in Python and R for vehicle and loan pricing strategies, boosting gross margins 70% YoY.
• •Oversaw auction analytics applications processing 200K vehicles daily to identify top margin candidates, doubling purchasing volume post-IPO.
• •Introduced company-wide CarvanaTalks program to advance data science best practices and cross-team collaboration.

Phoenix, AZ

• •Led multi-year transformation of the Auto and Mortgage Risk divisions into data-driven decision science functions through advanced modeling, portfolio analytics, and system automation.
• •Built and deployed loan-level forecasting and pricing engines in Python, Oracle, and SAS that modeled borrower cash flows and prepayment behaviors to estimate Net Present Value (NPV), Expected Loss, and Return on Assets across portfolios exceeding $200B.
• •Spearheaded the creation of an in-house Financial Engineering platform used during the Great Recession to establish optimal bid prices on distressed assets — enabling successful sale of $22B in loans to the secondary market.
• •Designed and validated credit risk segmentation, scorecards, and decision trees (CART, CHAID, Logistic, and ElasticNet models) to improve approval strategies and delinquency forecasting.
• •Partnered with Treasury and Finance to implement Basel II/III, CCAR, and stress-testing models for capital adequacy planning; served as technical liaison during OCC/FRB examinations.
• •Architected a data ecosystem and analytics layer (Teradata + Python microservices) enabling real-time portfolio diagnostics and early-warning indicators for loan performance.
• •Recruited and led a cross-functional team of 12 analysts and engineers, integrating model development, validation, and governance into a unified Decision Science framework across Auto, Mortgage, and Home Equity lines of business.