• Developed admin portals in React used by 100+ Dropbox corporate users to manage and analyze team activities.

• Implemented filters for time, member, and other key metrics in a team’s file-sharing activity table, achieving responsive design with a resizable filter component and “more/less filters” buttons for optimized UX across devices.

• Utilized feature flags to gradually roll out new functionalities across internal, beta, and production environments.

• Built Grafana dashboards to monitor user traffic and page errors. Set up auto alerts in Databricks SQL using historical user interaction data and server logs to detect performance regressions.

• Designed and built an admin console for 10+ engineering teams, managing over 1.8B Dropbox files and shared links.

• Created an universal search bar that resolves arbitrary input (shared link, filename, ID) to file entities, reducing page navigation by an average of 3 steps. Implemented matching algorithm in Python using regex and async HTTP lookups.

• Built detailed file metadata pages in React and TypeScript with rich navigating features, including storage info linked to DB tables, a tree view for recursive directory access history, and internal links connecting parent and child entities.

• Developed an access control mechanism to validate client identities and enforce file visibility permissions based on users’ team membership, integrating as authentication tokens into a backend server built in Python Tornado.

• Achieved 100+ internal users and reduced file-related bug investigation by 20+ mins per case.

• Developed analytics tools for AI platform developers to visualize e-commerce chatbot performance and usage metrics.

• Created interactive dashboards in Vue.js and Chart.js to display chatbot conversation statistics and user activity data in multiple chart formats. Supported historical performance analysis and side-by-side comparison against other models.

• Implemented dashboard filters based on timeframe, user profile, and product info for finer-grained analysis. Added "past queries" and "saved queries" features, with easy query sharing by embedding filter settings into dashboard URLs.

• Built a chatbot preview page displaying potential responses in a tree view to support corpus development. Improved page load efficiency by 3 seconds through lazy-loading of conversation data based on infinite scroll pagination.

• Supported the development of 5+ chatbot models and their deployment at 50+ client sites, reporting 1M conversations.

• Improved real-time Japanese-to-English machine translation with a sentence-final verb prediction algorithm in Python.

• Collected and cleaned input text of 330k sentences and utilized morphological analyzer to POS-tag word boundaries.

Achieved 92% verb prediction accuracy by training a bidirectional GRU and LSTM based language model in Keras.

• Further improved accuracy by 5% via shuffling Japanese phrase tokens to better represent natural colloquial variations.