Worked on software development for Workspace ONE Intelligence, a cloud service aimed at enhancing digital workspace environments through analytics, reporting, workflow orchestration, and insights for apps and devices
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Developed on microservice-based backend for digital employee experience features such as software asset management (SAM) and machine learning-driven anomaly detection and root cause analysis
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Conducted on-call rotations, including for release engineering and application, DevOps, and build stability issues
Transitioned from an internship to a full-time role with the Verizon Smart Family/Location Based Services team and continued to enhance the network geofencing algorithms and the web app developed during the internship
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Developed a web app for visualizing current and M-o-M changes in app ratings, reviews, customer escalations, and feedback survey results for the Verizon Smart Family app; led meetings to address customer pain points and drive resolution discussions
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Performed comprehensive evaluation on different mapping vendors by testing, comparing, and reporting on solutions
Conducted data analysis and created end-to-end machine learning pipelines (data cleaning, feature extraction, and classification) to derive exploitation insights from threat intelligence feeds and compare the performance of different machine learning algorithms
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Co-authored research paper with Siemens and Professor Zubair Shafiq
Developed four network geofencing algorithms that integrated intelligent GPS fallback to maintain geofence entry/exit precision, while avoiding over-reliance on device-based GPS queries; use case was for IoT devices
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Created a web app that ingested field test data, applied the algorithms, and visualized results and other pertinent information on an interactive map allowing for comparative analysis
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Presented geofencing algorithms to the VP of Consumer Product Engineering
