At Leap Scholar, I lead Analytics and Data Infrastructure, building a centralized seven-person function and an enterprise BigQuery platform spanning 800–1,000 raw tables, 50 curated models, and five business units. I established governed self-service analytics and revenue attribution, reducing ad-hoc reporting effort from roughly 80% to 10%.
I’ve built LLM-powered conversation intelligence that analyzes about 300 customer calls daily, improving second-call conversion by around 30%. I also developed predictive lead-prioritisation systems that lifted old-lead conversion by roughly 30% while reducing daily calling volume by about 80%.
Previously at Cure.fit, I led analytics, demand planning, forecasting, retention, and customer-experience intelligence as the business scaled online fitness. Across Amazon, Ocwen Financial Solutions, Cure.fit, and Leap Scholar, I’ve translated complex data into decision systems, data products, and measurable commercial outcomes.
