Leads the internal Applied AI product roadmap, translating operational challenges into AI applications, RAG implementations, agentic workflows, and automation systems. Partners with Finance, Operations, and go-to-market leaders to identify opportunities, define requirements and success metrics, collaborate with engineers and vendors, prototype solutions, drive adoption, and measure business impact. The role also oversees agile development, change management, reliability, and continuous improvement of internal AI tools.

Leads data science for growth marketing by building attribution, lifetime value, acquisition cost, retention, and predictive models. Designs A/B tests, geo-experiments, holdout tests, and incrementality studies to optimize marketing budgets and unit economics. Partners with Growth, Product, Finance, analytics, and engineering teams on data pipelines, event tracking, dashboards, and strategic decision-making. Applies causal inference, advanced analytics, and AI tools to drive user acquisition, retention, and profitable growth.

Leads engineering operations and strategy across a high-growth organization. Owns shared engineering processes, a $50M–$100M+ budget, vendor forecasting and relationships, strategic decisions, M&A technology due diligence, migrations, and cross-functional alignment. Partners with executives to resolve complex operational challenges, translate business goals into execution plans, and improve technology operations using AI tools and formal methodologies.