ABOUT ME
👋 A Computer Science graduate from the University of Southern California (USC), with over three years of industry experience at General Electric (GE), I developed scalable cloud-native products, boosting cloud admin productivity by 90%, and implemented a real-time monitoring framework, reducing person-hours by 80%.
My technical skills include Python, R, Java, Tableau, AWS, Data Structures and Algorithms, Object-Oriented Programming, REST API development, and Agile methodologies. My research includes predicting malicious activity in Android using machine learning and conducting NLP-driven political analysis of Subreddits.
I'm eager to contribute to a dynamic organization that values innovation. Contact me on LinkedIn for opportunities or project collaborations.✌️
TECHNICAL SKILLS
Amazon Web Services and Azure Cloud
Tableau Desktop and Tableau Server
Grafana and AWS QuickSight
Git
Ansible
Shell Scripting
NoSQL (MongoDB, DynamoDB)
Frameworks (Spring Boot, Spring MVC, Flask)
Object Oriented Programming and Design
Product Management, Design and Development
C & C++
HTML(5), CSS(3), JavaScript, Node JS, React JS, SwiftUI & Bootstrap
Data Structures & Algorithms
Programming with R
Core & Advanced Java
Python
Database Management Systems (MySQL, PostgreSQL, GraphQL)
Machine Learning & Natural Language Processing
PROFESSIONAL EXPERIENCE
• Improved Ansible-based infrastructure automation by fixing and enhancing existing playbooks for BIOS updates, OS deployment, and monitoring setup. Addressed and resolved Ansible lint errors to ensure consistency and maintainability.
• Developed and tested Ansible playbooks to automate OS flush and system reboots across multiple hardware platforms (Dell iDRAC and HP iLO), reducing manual intervention and standardizing deployment processes.
• Created and merged Ansible playbooks to automate containerized deployments (like Telegraf) across hosts, leveraging best practices for configuration management and reducing deployment complexity.
• Fixed lint errors and improved code readability across multiple Ansible files, updating workflows and enhancing documentation to maintain consistency and facilitate future enhancements.
• Developed and tested Ansible playbooks to automate OS flush and system reboots across multiple hardware platforms (Dell iDRAC and HP iLO), reducing manual intervention and standardizing deployment processes.
• Created and merged Ansible playbooks to automate containerized deployments (like Telegraf) across hosts, leveraging best practices for configuration management and reducing deployment complexity.
• Fixed lint errors and improved code readability across multiple Ansible files, updating workflows and enhancing documentation to maintain consistency and facilitate future enhancements.
WorkUp : Software Engineer Intern [May 2024 to July 2024]
• Enhanced user experience by implementing a feature that previews interview questions for selected categories before starting guided interviews, leading to improved user readiness and satisfaction.
• Redesigned the video recording feature to prevent automatic saving to the user's camera roll, reducing unintended media storage by 100% and improving user control over saved content.
• Fixed a bug causing 90% of portrait videos to rotate to landscape upon upload, ensuring proper video orientation and reducing user complaints related to video uploads by 100%, thereby enhancing overall user satisfaction.
• Redesigned the video recording feature to prevent automatic saving to the user's camera roll, reducing unintended media storage by 100% and improving user control over saved content.
• Fixed a bug causing 90% of portrait videos to rotate to landscape upon upload, ensuring proper video orientation and reducing user complaints related to video uploads by 100%, thereby enhancing overall user satisfaction.
University of Southern California : Viterbi Graduate Student Mentor [August 2023 to December 2024]
• Mentoring 1st Year Masters Students during thier first semester here at USC, Nominated for outstanding mentor Spring 2024.
General Electric : Software Enginner [July 2020 to December 2022]
• Architected and developed a scalable cloud-native solution leveraging AWS services to fortify cloud security round the clock, mitigating security risks and bolstering the productivity of cloud admin teams by 90%. Presently operational across 50+ AWS accounts, overseeing 40,000+ cloud objects, ensuring robust protection against data breaches.
• Spearheaded the development of two pivotal software projects: VERNIL, a comprehensive AWS inventory management system utilizing knowledge graphs, and Centralized Logging, a unified platform for streamlined log access and analysis across multiple systems and applications, benefiting operational efficiency and governance.
• Developed and implemented a cutting-edge real-time monitoring framework for ETL workloads, significantly improving efficiency by automating failure detection and resolution, resulting in an 80% reduction in person-hours.
• Implemented CI/CD integrated cloud infrastructure provisioning pipeline, slashing project creation and deployment time from 24 hours to under 5 minutes, boosting operational efficiency.
• Built an automated backup framework ensuring infrastructure integrity, cleaning irrelevant backups after 7 days, and significantly enhancing cloud platform availability.
• Led Tableau Platform Administration and served as Subject Matter Expert, overseeing platform migrations/upgrades and redesigning critical operations/support workflows to enhance efficiency.
• Automated over 15 dashboards in Tableau and Grafana, enhancing visibility into cloud platform compliance and infrastructure/application usage metrics, resulting in an 80% reduction in manual effort.
• Guided and supported interns throughout their internship, fostering their professional growth and contributing to their success in the program.
• Spearheaded the development of two pivotal software projects: VERNIL, a comprehensive AWS inventory management system utilizing knowledge graphs, and Centralized Logging, a unified platform for streamlined log access and analysis across multiple systems and applications, benefiting operational efficiency and governance.
• Developed and implemented a cutting-edge real-time monitoring framework for ETL workloads, significantly improving efficiency by automating failure detection and resolution, resulting in an 80% reduction in person-hours.
• Implemented CI/CD integrated cloud infrastructure provisioning pipeline, slashing project creation and deployment time from 24 hours to under 5 minutes, boosting operational efficiency.
• Built an automated backup framework ensuring infrastructure integrity, cleaning irrelevant backups after 7 days, and significantly enhancing cloud platform availability.
• Led Tableau Platform Administration and served as Subject Matter Expert, overseeing platform migrations/upgrades and redesigning critical operations/support workflows to enhance efficiency.
• Automated over 15 dashboards in Tableau and Grafana, enhancing visibility into cloud platform compliance and infrastructure/application usage metrics, resulting in an 80% reduction in manual effort.
• Guided and supported interns throughout their internship, fostering their professional growth and contributing to their success in the program.
• Improved database visibility, increasing team productivity by 70% through real-time alerts and automated reports.
• Architected and Developed data-flow architecture and process orchestration techniques, facilitating rapid development and deployment of ML models by Data Scientists and Engineers.
• Implemented a customized alerting framework integrated with ServiceNow and Active Directory for comprehensive cloud event monitoring, enhancing visibility with a 360-degree view.
• Implemented new features and facilitated migration of the internal Gamification web portal, enhancing user experience and ensuring seamless transition across AWS cloud accounts.
• Architected and Developed data-flow architecture and process orchestration techniques, facilitating rapid development and deployment of ML models by Data Scientists and Engineers.
• Implemented a customized alerting framework integrated with ServiceNow and Active Directory for comprehensive cloud event monitoring, enhancing visibility with a 360-degree view.
• Implemented new features and facilitated migration of the internal Gamification web portal, enhancing user experience and ensuring seamless transition across AWS cloud accounts.
• Devised a comprehensive E-Commerce portal following Spring MVC Architecture combined with NoSQL Database and Bootstrap for a responsive user interface, resulting in a 40% increase in website performance and a 20% boost in customer engagement via seamless user experience.
• Conducted code base reviews and resolved malfunctioning sections. Implemented a robust error handling mechanism, reducing system downtime by 30% and enhancing system reliability.
• Conducted code base reviews and resolved malfunctioning sections. Implemented a robust error handling mechanism, reducing system downtime by 30% and enhancing system reliability.
RESEARCH EXPERIENCE
NLP Driven Political Analysis of Subreddits [December 2022]
Machine learning has aided in the development of incredibly efficient solutions to today's complexities. It has virtually pervaded every field, and its potent solutions have substantially assisted humanity's growth. In this research, our prime objective is not to make the right predictions but to probe the different ways of applying the concepts of machine learning. We aim to comprehend the inner working of the models that aid in decision-making. Further, to meet the objectives of this research, we had to analyze a large text corpus. We implemented a fusion of algorithms with high interpretability to derive meaningful information from the data. To this end, we investigated approaches to extracting information from political subreddits using embedding-based sentiment analysis and feature analysis of a classification model.
Presented at 3rd International Conference on Data Intelligence and Cognitive Informatics. Link to the Research Paper
Presented at 3rd International Conference on Data Intelligence and Cognitive Informatics. Link to the Research Paper
Predicting malicious activity in Android using Machine Learning [May 2022]
The extent to which malware camouflages has begged the attention of a wide range of researchers all over the world to direct their attention to developing effective detection methods for the same. Current antiviral techniques, which are hash-based and heuristic-driven, do not appear to handle the problem efficiently or effectively. The remarkable success of machine learning in tackling this challenge has increased its usage in developing these detection systems. In this paper, we examine such approaches in order to assess the accuracy of ML-based methods, particularly in a supervised learning scenario, and to provide the reader with a systematization of knowledge on the current state of the field. In this paper, three different methods were proposed based on machine learning models to detect malicious programs, and we evaluated them to show their efficacy and efficiency.
Presented at International Conference on Computational Intelligence and Sustainable Engineering Solutions. Link to the Research Paper
Presented at International Conference on Computational Intelligence and Sustainable Engineering Solutions. Link to the Research Paper