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Click here or scroll down to respond to this candidateCandidate's Name
Orlando, FL PHONE NUMBER AVAILABLE EMAIL AVAILABLE LINKEDIN LINK AVAILABLE EDUCATIONUniversity of Central Florida Orlando, FLMaster of Computer Science GPA 4/4 August 2022 April 2024 Coursework: Design and Analysis of Algorithms, Machine Learning, Advanced Database Systems, Parallel and Distributed Systems WORK EXPERIENCESoftware Engineer August 2023 presentUniversity of Central Florida Orlando, FL Led the end-to-end development of a Python application to collect and process daily health metrics from 200+ Fitbit-equipped participants, generating a dataset of over 1 million data points for research insights. Developed robust integration with Fitbit Web APIs and Selenium leveraging OAuth2.0 authentication to retrieve user data from Fitbit trackers and utilized AWS Lambda for data aggregation. Designed and implemented Python Flask-based RESTful services to facilitate participant and authentication management services, slashing participant onboarding time by 75%. Software Engineer July 2020 August 2022Entain Group India Collaborated with a 5-member Scrum team to design and develop a market management platform, enabling Entain sports traders to streamline operations across 25 betting markets for 7 major US sports, including NFL, NBA and other top leagues. Architected a high-performance Reactive Java Microservice using Spring WebFlux, for real-time betting market data streaming, enabling market updates for over 5k concurrent traders with a 60ms latency via Server-Sent Events. Built scalable Spring Boot RESTful APIs for fixture/market management operations and integrated them with Kafka in an event- driven architecture for asynchronous processing, reducing the market response time from 12 sec to 5 sec. Implemented Redis cache (NoSQL) for concurrency control and mitigated data conflict errors by 90% during concurrent odds and pricing updates by traders, ensuring system accuracy and a seamless betting experience. Designed responsive UI components in AngularJS to display live scores by leveraging Event Sourcing and RxJS to consume real-time score feeds and provided user-friendly controls to streamline trader workflows. Software Engineer April 2019 July 2020Accenture India Contributed to the development of a centralized marketing system for 6 Belgian Distributed Grid Operators, focusing on writing business logic for both the Business layer and Data layer utilizing Asp.Net (C#) and Object-Oriented Programming. Led performance optimization efforts for a critical Billing module through targeted MySQL DB indexing and SQL query and stored procedure fine-tuning, significantly reducing database response latency from 33ms to 2ms. Implemented CI/CD through Gitlab, following DevOps best practices to ensure reliable integration, testing, and deployment for the platform and applied Agile Software methodology to streamline SDLC, utilizing JIRA for sprint tracking. Conducted comprehensive log analysis to identify root causes and troubleshoot bugs in the production environment, resulting in efficient bug resolution and improved system stability. Automated server monitoring and health check tasks through scheduled Cron jobs using Node.js, reducing the operations team overhead by saving 15 manual hours per month. SKILLSLanguages: Python, Java, JavaScript, HTML, CSS3, SQL Programming: Data structures and Algorithms, Object Oriented Design, Design Patterns Frameworks: AngularJS, Spring Boot, React.js, Junit Databases: Cassandra, MySQL, RedisTools: Jira, Maven, Docker, Postman, Swagger, Git, GitLab CI/CD Others: AWS, REST API, Kafka, OAuth, XML, DevOps, Agile methodologies, Software Development Life Cycle PROJECTSDashboard for all the MORD schemes, India Led a team of 4 to design a dashboard UI with charting capabilities using React.js, D3.js as frontend and Node.js as backend, enabling 200+ Indian Government officials to track key metrics about all the schemes of the Ministry of Rural Development in real-time.Cache Simulator Github link Developed a scalable Java cache simulator using Object Oriented Programming, supporting L1, L2, L3 caches with LRU, LFU, Optimal replacement policies, improving performance by 30% through LSTM model by forecasting future page requests. Clustering data to detect Network Intrusion Attacks using Genetic Algorithm Github link Implemented a research paper's findings to build a machine learning model utilizing Genetic Algorithm to classify network attacks into optimal cluster configurations, enhancing accuracy over traditional K-means clustering without exhaustive scenario evaluation. |
