Supported AIS Medicare IT Delivery Product Support Services.Consolidated an automated claims defects report in Excel, leveraging the data to build a dashboard that enhanced product support for clients. Additionally, created a Power BI dashboard sourced from Oracle SQL Server, delivering actionable insights to drive client satisfaction and operational efficiency.Proposed a 'Prediction, Prevention, and Profit' model to identify clients not using our Minute Clinic resource instead of outside clinics, projecting a potential profit increase by encouraging its usage for faster, easier doctor visits within their insurance plan.Created a Chatbot on the Microsoft 365 dashboard for Internal Product Support users as a guide.Created an automation report on Smartsheet from Salesforce for access log. Improved productivity by 30%Streamlined data management by migrating team data to Confluence and Jira, and automating Salesforce access logs, improving operational efficiency. Productivity was improved by 60%.Executed Linux scripting for file transfers and error handling, ensuring robust data management and system reliability.Supported AIS Medicare IT Delivery Product Services, contributing to team goals and enhancing cross-functional collaboration.Leveraged SQL, Power BI, and Splunk to analyze ServiceNow tickets and build dashboards, driving data-driven decisions for AIS Medicare IT Delivery.

Guided students through complex C++ data structures, enhancing comprehension and debugging skills. Developed targeted strategies to address common challenges in coursework.Analyzed student code to identify complex errors, enhancing debugging skills. Developed targeted strategies to address common challenges in C++ coursework.

Built a goggle that detects diabetes in a human based on size of pupils dilation.Engineered robust Python scripts to extract and measure pupil radius data from video files, enabling precise diabetes diagnosis.Implemented advanced rate-of-change analysis to accurately identify diabetic patients, significantly enhancing diagnostic capabilities.Utilized matplotlib to create insightful visualizations of pupillary responses, facilitating data interpretation and decision-making.Developed sophisticated Python algorithms to extract and analyze pupil dilation data from video files, enhancing accuracy in diabetes diagnosis.