San Francisco Bay Area
Ambitious, versatile engineer with seven years of professional experience in roles spanning industry and academia. My expertise lies in the intersection of data science, artificial intelligence, and software development.
Oracle Health AI - Agent Enablement Platform
Amazon Ads - IMDb Growth Analytics and Core Services • Involved in initiatives to design and develop services that drive engagement, reduce AWS cloud infrastructure costs, and improve operational excellence standards • Developed services to monitor and improve SEO performance and notification engagement; helped to increase search traffic by 8%, improved notification CTR by 91%, and decreased AWS costs by 15% YoY • Productionized a new AI-based email notification system leveraging anonymized user data, time-sensitive trends, and genre cohort models to deliver optimized recommendations
OCI Enterprise Performance Management - Planning and Budgeting Cloud Service (PBCS) • Implemented and maintained various features related to user preferences and metadata caching for Oracle SmartView, the Oracle EPM applications plug-in for Microsoft Office • Enhanced the functionality and reliability of outline load, hierarchy synchronization, and other heavily used workflows within the platform layer to improve the customer experience • Involved in developing a predictive performance analytics tool, leveraging a data pipeline, user-defined models, and Oracle AutoML to deliver useful insights for end users
Research Collaboration - Stanford NLP Group and Stanford Graduate School of Business • Worked on research project led by Prof. Gregory Martin and Prof. Shoshana Vasserman; findings were published in the Proceedings of the National Academy of Sciences • Created a multi-threaded pipeline to efficiently parse, aggregate, preprocess, and vectorize raw data from over 6 million newspaper articles stored within the Newsbank corpus • Experimented with FastText, GPT-based text classification, BERT Named Entity Recognition, dynamic LDA document influence models, and the latest Stanford CoreNLP methodologies to classify impact scores for works of investigative journalism with respect to award-winning articles
AT&T Entertainment Group - Open Video Innovation • Developed microservices to scrape, aggregate, and analyze product-specific text data from real-time social media feeds, as well as a corresponding iOS application to graphically display and monitor customer sentiment trends worldwide • Created a data pipeline to query, parse, cluster, and analyze terabytes of data from billions of DirecTV NOW user sessions; utilized DBSCAN, random forests, and other machine learning models to analyze customer satisfaction trends and identify features associated with negative user experiences