● Managed a data science team of two managers and eight analysts to support several aspects of new account origination including pricing, credit risk, residual value risk, fraud, and profitability.● Developed a suite of models to optimize pricing in order to maximize expected profit, taking into consideration risk, and customer demand. Due to a lack of good experimental data, a method similar to propensity score matching was used in order to make observational data more closely resemble experimental data. Models were then estimated for elasticity of demand, charge-off, early pay off, and the profit associated with each event.● Managed a data science team for consumer credit risk focusing on new account originations. Worked closely with the strategy team in Risk as well as the Sales department to ensure all models met their needs.● Developed a new predictive model for originations risk using a modular, ensembled approach. Separate models were built using bureau data, and application data, for both the primary applicant and the co-applicant. These models were then combined into a final risk score for the loan.● Deployed a new decision engine for loan originations using open source resources (Python) to replace legacy Experian decision engine (Experian Strategy Manager). This included the newly developed originations risk model, as well as all credit rules, fraud rules, legal rules, etc. Worked closely with IT to deploy in the cloud using Kubernetes (within AWS).● Built framework for interpretable machine learning models for credit granting decisions in order to provide adverse action reasons regardless of model estimation technique.● Developed first originations risk model for Mazda Financial Services, and Bass Pro Shop Financial Services.● Model Governance – one of five governance team leads overseeing model peer review across TFS.

● Responsible for collections risk strategy development within the Global Modeling & Risk Analytics team for Citi’s Mexico portfolio (Banamex)● Established optimal collections contact strategy using conditional probability to calculate the Expected Value maximizing strategy● Developed new account-level risk segmentations for credit cards & installment loans early stage delinquency● Optimized external agency account placement using scores & segmentation to profit maximize collection effort

● Manager of the predictive modeling team for Credit One Bank. Managed 4 other model developers to service various departments within the bank by creating models to predict credit risk, fraud risk, response to marketing campaigns, revenue, credit card usage, attrition, collections, customer service call volume, macroeconomic stress testing, etc. which has generated tens of millions of dollars in incremental profit over 2 years.● Designed first underwriting strategy for the bank for prime customers.● Designed the bank’s first custom acquisition fraud & custom transaction fraud models.● Created the first suit of models for the bank using demographic and geo-aggregated credit data● Redesigned the collections strategies (decision trees) to accommodate new vendor scores● Created an algorithm for assigning optimal credit lines at the time of underwriting● Maintain the model used for reserves against loan losses and audit of method accuracy● Developed first macroeconomic stress test model for the bank using Vector Autoregression (VAR)

● Taught Principles of Macroeconomics for 6 semesters to large classes (greater than 120 students)● Received student-based reviews substantially higher than the college and department averages: 4.77/5.00 compared to 4.14/5.00 for the economics department and 4.24/5.00 for the college.● Teaching assistant for several higher-level economics courses: Forecasting, International Trade, International Macroeconomics and Finance, and Graduate Macroeconomics I.● Research assistant on Center for Business and Economic Research Projects: “Reviewing Arkansas’s Position in the Knowledge-Based Economy” (2011) and “Estimating the Economic Impact of the Mercy Health System in the State of Arkansas” (2010), writing, revising, collecting and analyzing data.