Data Analyst with AI

§ Build and maintain HEART dashboard views with division-level and BU-level drill-downs. § Analyze AI adoption across divisions, including active users, new users, repeat users, usage frequency, session depth, task completion, and adoption trends. § Create cross-division comparison views 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 views for top users by division, top GPT creators, AI Champions, power users, and emerging adoption pockets. § Develop AI Champions self-service dashboard views with filters, exports, and role-based reporting by division or BU. § Analyze token economics by model, BU, use case, application, provider, and time period. § Build spend and consumption reports showing forecast vs. actual spend, cost per user, cost per GPT, cost per use case, token intensity, and quota utilization. § Identify abnormal usage patterns, high-cost use cases, model inefficiencies, and opportunities for model rightsizing. § Create observability dashboards for RAG and AI infrastructure, including latency, error rates, pipeline freshness, indexing status, retrieval issues, and availability trends. § Support dashboard UAT, metric validation, data reconciliation, and stakeholder walkthroughs. Translate analysis into actionable recommendations for AI Ops, AI Champions, finance, and leadership