Key Accountabilities:● Responsible for providing galvanizing leadership to a data science team, machine learning engineering team, and a credit risk and analytics team effectively developing their capabilities and expanding their responsibilities● Relied upon to seamlessly collaborate with CFO to develop and implement our pricing strategies● Depended upon to manage production machine learning models ensuring targets business objectives are met

Key Accountabilities:● Responsible for providing galvanizing leadership to a team of data scientists, a team of data analysts, and a team of BI developers effectively developing their capabilities and expanding their responsibilities● Relied upon to seamlessly collaborate with CFO and Pricing Committee to develop and implement our pricing strategies● Depended upon to manage production machine learning models ensuring targets business objectives are met● Proficient risk counterpart for the originations committee, servicing committee, pricing committee and executive credit committee

Key Accountabilities:● Responsible for providing galvanizing leadership to a team of data scientists and analysts, effectively developing their capabilities and expanding their responsibilities● Relied upon to seamlessly collaborate with CFO and SVP of Structured Finance to transition the ALLL (allowance for loan and lease losses) to follow CECL (current expected credit losses) guidelines● Depended upon to manage production machine learning models ensuring targets business objectives are met● Proficient risk counterpart for the originations committee, IT steering committee and executive credit committeeKey Accomplishments:● Engineered the development and deployment of four machine learning credit scoring and pricing model reducing vendor costs by over $1M per year● Supervised the creation of an NLP model used to monitor collectors text messages for compliance violations; monitors 2.9M text messages per year, 73% decrease in potential compliance violations● Mentored a direct report in the creation of enhanced net loss forecasting models using state of the art machine learning and natural language processing models; reduced error rate from 30% to 5.5% at time of funding● Created a book value prediction model that predicts the book value of a vehicle with an error of 7%. Used to populate the book value of vehicles on the inventory page of our new dealer portal. Pulling the actual value for each dealership and all vehicles on their lot would cost roughly $120,000 per year.

Key Accountabilities:● Responsible for accurately developing and monitoring new credit underwriting models to approve applicants● Relied upon to create or improve departmental reporting capabilities, effectively educating stakeholders with data-visualization and predictive modelingKey Accomplishments:● Orchestrated process improvements including the removal of an outdated secondary pricing system; System decisioning increased from 77% to 88%; Approval Rate increased from 28% to 32%● Innovated cumulative net loss forecast improvements; Old method = loss timing curve only; New method = combination of loss timing curve, regression, probability of default/exposure given default/loss given default● Championed monthly net loss projection improvements by transitioning from using static pools and roll rates to an ARIMA model, which resulted in decreasing MAPE from 22% to 8.5%● Successfully distilled Risk Summary into a focused presentation of application statistics, monthly loss projections, vintage loss projections, recovery performance, early performance summaries, and collections statistics● Consistently received annual promotions, from Risk Analyst I to Risk Analyst II, then Risk Analyst III, and most recently into Vice President role

• Teaching Assistant for Stat 462: Quality Control and Industrial Statistics• Teaching Assistant for Stat 512: Stat Methods for Research 2

• Research on belonging among junior high students using cluster analysis

• Filed and pulled patient charts for the following day• Filed insurance paperwork• Performed lab work on cad cam machine• Made crowns

• Made purchases of medical supplies while adhering to a budget• Analyzed the cost of surgeries and looked for areas for improvement• Stocked medical supplies