• Developed full stack (React frontend Python backend) AWS based LLM for financialguidance using AWS Serverless Infrastructure Management (SAM).• Designed vector databases for RAG implementation, CI/CD framework for deployment,Lambda functions for Bedrock LLM API calls, and APIs with endpoints.• Integrated backend and UI with PLAID API to connect with financial institutions and provide more personalized and secure financial guidance.• Tested various LLMs based on human expert evaluation.• Awarded AWS founder credits for business case and progress.

[Public Trust Clearance]• Provided mentorship on data product management to a team of 3 product managersand 9 data analysts.• Worked with Veterans Affairs Loan Guarantee data organization on drafting acomprehensive data strategy as well as POCs for behavioral modeling and forecasting.• Co-wrote 4 proposals and crafted POCs for potential clients on LLM synthetic data.

• Leader of B2B and B2C product research, exploration, and ML development teams forthe payments and embedded finance organization• Oversaw A/B testing for BU, leading to a 60% increase in testing quality for customerfacing products.• Led exploration of LLM use cases for code development.• Led transition to real time data solutions and live ML decisioning.• Drove ML and data engineering of real time FX product personalization that unlocked~€140 million in revenue over 2022-2023 (on ~$15 billion monthly volumes).• Performed hands-on business analysis of product opportunities and presentedroadmaps and value propositions to senior stakeholders.

• Product manager of 20 member delivery team, from ideation to final implementation, fornew Allowance (CECL) model for $115 billion card portfolio from 2018-2020.• Awarded Circle of Excellence in 2020 for successful delivery and business impactwhich reduced income volatility by >$1 Billion per year.• Owned model methodology communications with the OCC and FRB.• Senior Model Risk leader for high risk regulatory models from 2013-2017 leading thevalidation and report writing of over 20 time series and ML models for variouscustomers across the enterprise.• Presented at internal conferences on best practices in time-series modeling.

I owned the responsibility for developing marketing and pricing strategies for the credit card portfolio. This involved leading a team of decision scientists developing a new predictive model to determine line management strategies to reduce customer balance and spending attrition. This strategy went on to solve a long term company objective which provided me the opportunity to present my strategy to the president of the US Card business.

I began as the lead MIS programmer to automate company wide risk reports. I then moved on to become the lead model developer of line management strategies for HELOC and credit cards and the loss forecasting analyst for mortgages. I was then promoted to lead modeler for the Allowance forecast and served on the quarterly allowance committee alongside the CRO and CFO. In addition to my core responsibilities I utilized my background in SAS software development to teach a month long course on SAS programming to 20 business partners, including senior management, saving estimated training costs of $120,000 (based on equivalent courses provided by SAS).

Working in the retail solution development group I developed and validated demand forecasting models for several national and international retail customers. These solutions were packaged and sold as software solutions to be run by SAS's internal consultants. In addition I was tasked with developing validation programs to evaluate the models and monitor their on-going performance.