• Built and deployed machine learning models for fraud detection and predictive analytics

• Designed real-time data pipelines using Kafka processing 10,000+ transactions/min

• Deployed ML models using Docker and Kubernetes with auto-scaling

• Improved database performance by 60% through schema optimization

• Built backend services and APIs handling 1,000+ requests/sec

• Implemented OAuth2 and JWT authentication for secure deployments

• Developed and optimized a high-performance financial trading platform, reducing latency by 30% and improving real-time data processing

• Designed and implemented scalable microservices architecture using Java and Spring Boot, improving system efficiency and reducing response time by 30%

• Built real-time data pipelines using Apache Kafka, enabling seamless processing and streaming of high-volume financial data

• Developed RESTful APIs using Python (Flask, Django) to support frontend-backend communication in distributed systems

• Integrated MongoDB for scalable data storage, ensuring high availability and performance for large datasets

• Collaborated with cross-functional teams in Agile (Scrum) environment, reducing feature delivery time by 25% through CI/CD automation using Jenkins

• Designed and enhanced user interfaces using Angular, improving user engagement and overall application usability

• Built an AI-driven recommendation engine for an e-commerce client, improving customer engagement by 20% and reducing response time by 35%

• Leveraged AWS services including S3 for secure cloud storage and efficient data management