Sravani Raghavaraju

Software Developer @PayPal

TX, US

Designed and implemented real-time fraud detection microservices using Java 8, Spring Boot, and Apache Kafka, enabling the processing of over transactions per minute with low latency. • Created scalable MongoDB schemas and aggregation pipelines to store and query user behavior logs and transaction metadata, enabling fast fraud analytics and improving data retrieval performance by 12%. • Developed responsive React.js dashboard using Redux, Chart.js, and Material UI to enable internal risk analysts to visualize flagged transactions, behavioral anomalies, and historical fraud trends, improving data-driven investigation workflows and increasing analyst efficiency by 25%. • Improved fraud detection efficiency by 10% over six months by refining scoring models and optimizing service response times for risk-sensitive operations. • Enhanced analyst workflow efficiency by 5% through the development of interactive dashboards and real-time alerting mechanisms integrated with PayPal’s fraud intelligence tools. • Applied secure API authentication and authorization using OAuth 2.0 and JWT tokens, ensuring secure access to fraud analytics and internal tooling by analysts and backend systems. • Integrated third-party APIs (IP geolocation, device fingerprinting) within Node.js services to capture contextual data such as location, browser, and device type—enhancing fraud scoring accuracy and reducing false positives in real-time detection. • Configured AWS S3 to securely store historical transaction logs and fraud audit reports with encryption and lifecycle policies, supporting compliance needs and reducing long-term storage costs through automated archival to Glacier. • Built CI/CD pipelines using GitHub Actions and Jenkins, automating build, test, and deployment processes and reducing release cycles by 30%.

University of North Texas

Master of Science - MS

Sathyabama University

Computer Science

Sathyabama Institute of Science & Technology, Chennai

Bachelor's degree