Sai .. Email & Phone Number

Irvine, CA, US

• Engineered a patient management application using Python and Flask, incorporating API integrations to automate data handling, streamline patient information access, and enhance decision-making for healthcare teams.
• Created and fine-tuned RESTful APIs with Python and Flask to strengthen backend services, supporting efficient data transfer and smooth integration across applications.
• Built responsive front-end features with React and JavaScript, elevating user experience and boosting client-side performance.
• Managed both relational (Oracle DB) and non-relational (MongoDB) databases, optimizing data storage, retrieval, and indexing to ensure high availability and reliability.
• Designed and deployed scalable, serverless applications leveraging AWS services like Lambda, S3, EC2, and ECS, maximizing cloud infrastructure performance.
• Automated backend workflows with AWS Lambda, Step Functions, and API Gateway, enhancing real-time data processing and minimizing response time for healthcare applications.

• Built a comprehensive risk analytics platform using Python and Flask, creating RESTful APIs to provide real-time risk insights for financial instruments, supporting strategic decision-making across departments.
• Designed a microservices framework using Flask and Docker, modularizing key components like data ingestion, risk scoring, and portfolio analysis for improved scalability and resilience.
• Developed predictive risk models in Python with Scikit-learn, integrating machine learning to forecast financial risks such as credit defaults and market volatility.
• Managed and scaled risk-related datasets in MongoDB, efficiently handling both structured and unstructured data to enable complex, real-time queries.
• Automated AWS infrastructure provisioning with Terraform, streamlining the deployment and scaling of resources like MongoDB clusters, S3 buckets, and EC2 instances.
• Deployed serverless functions with AWS Lambda and used Amazon SQS for asynchronous messaging, enabling efficient, cost-effective event-driven processing for real-time portfolio and risk management.

• Built backend functionality in Python for automotive software, processing real-time data to enable features like energy optimization, diagnostics, and vehicle performance improvements.
• Enhanced front-end capabilities with Python frameworks, creating responsive UIs for automotive systems to provide seamless data access and visually intuitive experiences for end-users.
• Developed dynamic, interactive interfaces in React and Python, leveraging real-time data visualizations to boost user engagement and operational efficiency.
• Managed relational and NoSQL databases by designing schemas, writing complex queries, and utilizing Python libraries to perform efficient data manipulation and retrieval.
• Deployed and managed cloud infrastructure using AWS services like EC2 and S3, optimizing resource management for scalable and secure Python applications.
• Created custom UI components, including data tables and interactive controls, tailored for monitoring and managing vehicle performance metrics within Python applications.