ABOUT ME
Data, analytics, and AI leader with 13+ years translating complex business problems into measurable business impact through analytics, AI, data platforms, and operational improvement.
Experienced developing business cases, KPI frameworks, executive scorecards, and benefit-tracking methodologies; structuring ambiguous problems; influencing senior leaders; and leading cross-functional initiatives across product, engineering, operations, finance, and business teams.
Selected Data, Analytics & Business Performance Initiatives
Built enterprise analytics and executive reporting capabilities that connected customer, operational, and performance data. Developed KPI frameworks, scorecards, and dashboards in Power BI and Tableau to identify performance gaps, monitor business outcomes, and translate quantitative findings into actionable recommendations for senior leaders.
Designed a closed-loop operating model that converted low customer scores into prioritized cases, owner accountability, follow-up actions, and outcome measurement. Used analytics to quantify impact, surface operational risks, and support business cases for process and service improvements.
Developed a centralized DataMart integrating customer, operational, and transactional data to support advanced analytics and decision support. Improved analytics acumen across stakeholders by enabling deeper root-cause analysis, KPI development, and more rigorous measurement of business performance.
Built data-driven recommendation and discovery capabilities that generated more than $80M in attributed revenue. Used behavioral data, experimentation, and performance analytics to improve relevance, support commercial decisions, and demonstrate measurable business impact.
AI, Automation & Decision Intelligence
Applied generative AI and LLMs to synthesize high-volume customer and operational data into concise insights, trends, and executive narratives. Accelerated analysis while improving the speed at which senior leaders could identify business risks, opportunities, and recommended actions.
Developed AI-enabled knowledge and conversational experiences using enterprise data, retrieval, and analytics. Defined success metrics, monitored answer quality and adoption, and used behavioral data to improve relevance, usability, and measurable business outcomes.
Used AI voice-to-text and analytics to convert customer interactions into structured data for analysis. Automated insight generation across service conversations, enabling stronger KPI reporting, root-cause analysis, and operational decision support.