Anith Joy

Developed Python data analysis modules to identify patient scheduling bottlenecks, improving resource allocation by 15%. Designed RESTful APIs with Django REST Framework to enhance hospital system interoperability, reducing redundant data calls by 25%. Automated HIPAA compliance checks during data migration using Python scripts with full regulatory adherence. Optimized queries and caching to reduce API latency by 1.8 seconds. Built an AI appointment scheduler using AWS Lambda handling 50,000 daily requests and improved scheduling accuracy. Implemented a real-time alert system with Python Socket.IO and React.js, reducing emergency response times by 15 minutes per case. Automated testing workflows with PyTest and Selenium, catching and fixing critical bugs pre-deployment.

Developed Python data analysis modules improving clinic resource allocation by 15%. Designed RESTful APIs with Django REST Framework, reducing redundant data calls by 25%. Automated HIPAA compliance checks during data migration and optimized queries for patient data systems cutting API latency by 1.8 seconds. Built AI appointment scheduler handling 50k daily requests using AWS Lambda. Implemented real-time alert system using Socket.IO and React.js, reducing emergency response times. Automated testing workflows identifying critical bugs pre-deployment.

Developed Python data analysis module using Pandas to identify patient scheduling bottlenecks, improving clinic resource allocation efficiency by 15%. Designed RESTful APIs with Django REST Framework to improve hospital system interoperability, reducing redundant data calls by 25%. Automated HIPAA compliance checks during data migration using Python scripts, ensuring 100% regulatory adherence. Optimized queries and caching for HIPAA-compliant patient data system (Django/PostgreSQL), reducing API latency by 1.8 seconds. Built Python-based AI appointment scheduler with AWS Lambda, handling 50k daily requests and improving scheduling accuracy. Implemented real-time alert system using Python Socket.IO and React.js, reducing emergency response time by 15 minutes per case. Automated testing workflows using PyTest and Selenium, identifying 12+ critical bugs pre-deployment.