● Manage group of analyst responsible for all portfolio and lease remarketing analytics.● Developed suite of pricing models that prices all US and Canadian vehicles in portfolio● Principal duties included working with business partners to formulate problems while overseeing analytic methodologies, and initiating projects through researching and modeling data.

Ensure the successful implementation and management of machine learning operations, data governance practices and experimentation projects within the data science department.

• Residual Value Forecasting – Developed Lease Buyout (LBO) model for lease portfolio, logistic model incorporating leasing industry data / experience and macroeconomic variables• Co-developed Extreme Mileage and Excess Wear models to be used in Remarketing pricing strategies• Residual Value Forecasting - Developed the firm’s residual model along with accompanying documentation for model review along with CCAR and DFAST scenarios to support residual setting or remarketing optimization• Residual Value Risk Analysis - monitored residual value lease residual risk and lease profitability, including: front-end pricing, internal costs, monthly auction values of leased automobiles, and vehicle remarketing• Model Validation - worked in conjunction with the model governance to ensure adequate testing and data validation of any model enhancements• Streamlined existing code for Business Planning as well as weekly, monthly and quarterly reports

• Developed Loss Forecast Models for ALLL, Stress Testing, CCAR, and DFAST for Economic Capital purposes on $55B+ auto loan portfolio.• Statistical Models are built using loan level information (224M+ records) to derive hazard ratios for Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models.• Documentation accompanying all loss forecast models to the Federal Reserve and OCC.• Present and communicate loss forecast model theory, methodology, and results during meetings with the Federal Reserve and OCC. • Co-developed multivariate regression model that requires leasing industry inputs and macroeconomic variables to derive a residual value forecast.• Data Integrity officer responsible for BASEL Capital Calculation submission• Oversaw and drove data governance and data management programs/initiatives.• Residual Value Forecasting - co-developed the firm’s residual model using multivariate regression methodologies - and incorporating leasing industry data / experience and macroeconomic variables to derive a residual value forecast• Pricing Recommendations - provided recommendations to the firm’s senior managers based on monthly and quarterly projections and included ad-hoc analysis tracking and monitoring general economic and market factors affecting current and future auto prices • Residual Value Risk Analysis - monitored residual value lease residual risk and lease profitability, including: front-end pricing, internal costs, monthly auction values of leased automobiles, and vehicle remarketing• Trends and Performance Tracking - established historical performance trends within vintages and other segments (model, model year, term)• Residual Value Model Updates - analyzed and reported on residual value model monthly updates • Model Validation - worked in conjunction with the model governance to ensure adequate testing and data validation of any model enhancements

o Analytical risk specialist – analyst covering a portfolio of 8 million residential mortgage accounts; default analytics associated with Home Lending portfolioso Collaborated with management by preparing ad hoc analyses and monthly policy exception and performance reportingo Provide senior management with expanded reporting, risk/reward modeling, and over-arching portfolio risk analysiso Modeling - developed gain-loss model for homes in different stages of distress

Mandated on various contract engagements undertaken with the Phoenix-based, Humana unit launched in 2006 – a national mail order retail pharmacy business (Right Source) – as its business was expanding.o Partnered with the management team to develop and implement projects and programs designed to result in higher quality, cost reduction and continuous performance improvement.o Ensured that appropriate research design and quantitative and qualitative statistical methods are used in analyseso Analyzed and reported on quantitative and qualitative data using SAS and Minitabo Worked across teams to research issues and makes recommendations to improve policies or procedures to management.o Team Leader – served as Statistical and Mathematical Model Validation Team Leader.

• Established and standardized all operations and procedures for 13 business units• Forecasting Models - prepared forecasting models of growth potential in the Phoenix area using SAS• Analyzed and reported on quantitative and qualitative data to ownership including trends, opportunities and evolving business environment.• Used statistical and data mining techniques (Multivariate Analysis and Clustering) to improve product offerings, specially customer profile• Trained and developed Managers and staff through certification program and other performance metrics

o Created, oversaw and analyzed survey data about consumer purchase reasons using SAS and other statistical programso Developed customer segmentation and profile analysiso Handled adhoc projects as requested by management to interpret business needso Communicated technical concepts clearly, concisely, and understandably to non-statistical executiveso Worked on developing Statistical models that would accurately predict Nissan’s stance in the JD Power Initial Quality Survey (IQS) and the JD Powers Automotive Performance, Execution and Layout (APEAL) report.