•Directed Python-driven QA testing using PyTest and Selenium, boosting quality by 25% and decreasing bugs by 60%.• Led the integration of OAuth2 and Python security frameworks, reducing vulnerabilities by 20% and improving user authentication processes.•Overhauled client-side API with Python and Flask, employing GraphQL to increase data query responsiveness by 25% and support over 100,000 monthly users. • Refined data models and SQL interactions in Python, enhancing transaction speed by 15% and dataretrieval efficiency by 20% with MS SQL Server optimizations. • Designed and deployed over 25 microservices using Python and Django, achieving a 20%reduction in system latency and improved scalability for complex service-oriented architectures. Integrated and ensured performance across all service layers at PetSmart.

•Developed and deployed scalable Python-based applications for industrial AI platforms, enhancing predictive.• Integrated PostgreSQL with Python to create robust data pipelines, enabling real-time processing of live data feeds.• Collaborated with cross-functional teams to integrate Python solutions with existing systems, improving data accessibility.•Implemented machine learning algorithms in Python to optimize production schedules, reducing downtime by 25%. •Maintenance and operational efficiency by 15%. Led the design and implementation of Python-driven front-end solutions using React and AngularJS for real-time risk.•Conducted performance tuning and debugging of Python applications, resulting in a 20% increase in processing speed.

• Achieved 85% accuracy in mobile-based skin disease detection by implementing TensorFlow and CNNs.• Developed a heartbeat noise reduction algorithm in Python, improving preprocessing accuracy for detecting heart conditions from smartphone-recorded stethoscope sounds.• Integrated MySQL with the backend to store and manage training/testing data file paths and user activity data, ensuring seamless access and retrieval for real-time AI inference and training.