•Integrated LLM-powered chatbot functionality into the SWAP platform (a resource sharing platform for non-profit organizations), which helped users find matching resources based on past postings. This made it 45% easier to discover matches and increased successful resource exchanges by 35%. •Used the chatbot to suggest which users might need or have certain items, based on earlier sessions. This helped users make faster decisions (30% improvement) and led to 25% more activity on the platform.

•Analyzed large language model (LLM) data to quantify and reduce bias using SEAT and intersectional bias metrics, showcasing expertise in data analysis and interpretation. •Implemented self-de-biasing techniques, achieving a 20% reduction in bias for English LLMs and 15% for Spanish LLMs, reflecting strong analytical thinking and data-driven solution development.

•Interpreted large datasets using SQL and Python, optimizing data workflows and supporting data-driven decision-making to streamline business processes. •Managed test data ingestion and transformation to ensure high-quality analytics and reliable reporting, leading to enhanced and targeted automated testing frameworks in Python and Java

•Programmed a web-based predictive model for thyroid disease diagnosis with 94% accuracy, demonstrating proficiency in predictive analytics •Automated test cases, enhancing application reliability by 25% and reducing defect rates by 20%, showcasing skills in quality assurance and efficient data processing.