Data Analyst with AI

Build and maintain HEART dashboardviews with division-level and BU-level drill-downs.

Analyze AI adoption across divisions,including active users, new users, repeat users, usage frequency, sessiondepth, task completion, and adoption trends.

Create cross-division comparisonviews for leadership to identify high-adoption groups, low-adoption groups,enablement needs, and AI maturity patterns.

Analyze user-created GPT activity,including creation trends, usage frequency, most-used GPTs, underused GPTs,stale GPTs, reclaim candidates, and replication opportunities.

Create leaderboard and cohort viewsfor top users by division, top GPT creators, AI Champions, power users, andemerging adoption pockets.

Develop AI Champions self-servicedashboard views with filters, exports, and role-based reporting by division orBU.

Analyze token economics by model, BU,use case, application, provider, and time period.

Build spend and consumption reportsshowing forecast vs. actual spend, cost per user, cost per GPT, cost per usecase, token intensity, and quota utilization.

Identify abnormal usage patterns,high-cost use cases, model inefficiencies, and opportunities for modelrightsizing.

Create observability dashboards forRAG and AI infrastructure, including latency, error rates, pipeline freshness,indexing status, retrieval issues, and availability trends.

Support dashboard UAT, metricvalidation, data reconciliation, and stakeholder walkthroughs.