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.

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.

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.

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

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