Real-Time Fraud Detection & ML Analytics Platform
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Summary
Designed and implemented a real-time fraud detection system leveraging Python, machine learning, and stream processing technologies to analyze transactional data.
A highly skilled Software Engineer specializing in backend development and scalable systems, leveraging expertise in Java, Spring Boot, and microservices architecture. Proven ability to deliver high-performance RESTful APIs and integrate machine learning models, significantly enhancing system efficiency and product relevance for large-scale user bases. Seeking to drive robust, data-driven services that accelerate product innovation and deliver measurable business impact.
Software Engineer
USA, USA, US
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Summary
Currently leading backend development and API optimization using Java and Spring Boot to enhance product recommendation systems and improve service stability for a large consumer base.
Highlights
Developed and optimized high-performance RESTful APIs using Java and Spring Boot, reducing average response times by ~30% through advanced query optimization and Redis caching.
Contributed to critical backend services supporting product recommendation workflows, serving tens of thousands of daily users and processing over 10,000+ SKUs daily.
Integrated complex machine learning models for product recommendation scoring, boosting recommendation relevance by 15% across a large-scale consumer platform.
Analyzed and tuned JVM performance, identifying inefficient API flows and contributing to measurable improvements in service throughput and stability.
Collaborated cross-functionally with senior engineers, architects, and business analysts to deliver multiple enterprise features on time, enhancing system performance and aligning with key business goals.
Streamlined CI/CD pipelines by implementing automated SonarQube security scans and integration tests, successfully reducing production incidents by 40%.
Software Engineer
Bengaluru, Karnataka, India
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Summary
Developed and maintained enterprise web applications using Java and Spring Boot, optimizing backend performance and enhancing user experience for over 50,000 daily active users.
Highlights
Engineered and maintained enterprise web applications using Java, Spring Boot, and Hibernate, supporting systems with over 50,000 daily active users and ensuring high availability.
Optimized backend performance by ~30% through strategic SQL query tuning, indexing, and connection pooling across MySQL and PostgreSQL databases.
Developed responsive frontend components with React and Next.js, significantly improving user usability and reducing customer support inquiries.
Integrated frontend applications with backend APIs using Axios and Fetch, enhancing data retrieval speed by 30% and delivering smoother, faster user experiences.
Implemented robust authentication and authorization mechanisms (OAuth2, JWT) to strengthen user access security and prevent unauthorized requests.
Authored comprehensive unit and integration tests using JUnit, Mockito, and Selenium, increasing code coverage and reducing post-release defects.
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Master of Science
Data Science
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Bachelor of Technology
Computer Science
Java, Python, JavaScript, TypeScript, C#, Golang, C++.
Spring Boot, REST APIs, Hibernate, .NET, Next.js, Node.js, GraphQL.
React, HTML, CSS, Tailwind, Vue.js, Angular.
MySQL, PostgreSQL, MongoDB, Redis.
AWS (EC2, S3, RDS, Lambda), Docker, CI/CD (Jenkins, GitHub Actions), Azure, Kubernetes.
Git, Agile/Scrum, Unit Testing (JUnit, Mockito), Datadog, Distributed Systems.
Microservices Architecture, RESTful API Design, Database Design, Performance Tuning.
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Summary
Designed and implemented a real-time fraud detection system leveraging Python, machine learning, and stream processing technologies to analyze transactional data.
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Summary
Developed a scalable, high-performance microservices-based e-commerce platform designed to handle substantial transaction volumes.