Honored to work with great people on an exciting application of cutting edge technology

• Lead a team of 5 engineers to design and deploy custom AWS architectures for an AI application that pulls userpayroll and tax data then delivers customized tax and financial solutions supported by cited IRS publications• Implement Retrieval-Augmented Generation (RAG) with Pinecone, Open Search, and Aurora vector DB's on AWSKnowledge Bases by scraping, chunking, enriching, embedding and vectorizing 2,400 IRS PDF publications.• Utilize prompt engineering methodologies from Open AI and Anthropic documentation to tailor model behavior• Leverage Anthropic tool use methodologies to make multiple vector databases and APIs accessible to a central model• Fine-tuned Llama 70B model on AWS SageMaker using generated QA pairs in a feature extraction methodology

-Optimized competitive price points for new merchants by using machine learning to predict 5 unit economics-Created a regression analysis using machine learning that predicted the percent of customers at a merchant who would be new to Klarna with 90 percent accuracy which was used to target growth merchants and mitigate risk-Worked with internationally based data engineers to create a model that identified underperforming merchants based on metrics in their user experience journey using a large Excel model which queried from our database using SQL

-Focused on sourcing early-stage investments from Seed to Series B emerging technologies companies-Reached out to and interviewed CEOs and founders to collect KPI’s and analyze business models-Built and presented diligence decks to limited partners resulting in one deal with 5X return on investment

-Wrote content for 4 large clients including a leading automotive maker, a hotel brand, and a consulting firm-Conducted market research, evaluated competitive and market landscapes, and made strategic recommendations -Worked as part of a new business team to pitch and win a new contract with Citi Bank to redesign their app