• Set the company-wide strategy for product analytics, business metrics, and GTM insights • Define the core measurement frameworks for product usage, activation, retention, expansion, and customer value • Ensure analytics meaningfully influence product roadmap decisions, GTM strategy, and operational planning • Oversee the delivery of trusted dashboards, reporting, and self-serve analytics used by executives and functional leaders • Establish standards for metric definitions, data quality, and analytical rigor across the organization • Lead the data engineering strategy in close partnership with data engineers • Set expectations and priorities for how data engineering supports analytics, product insights, and ML use cases • Ensure the data foundation (ingestion, modeling, storage, governance) scales with the business and product needs • Act as the primary stakeholder for analytics requirements, guiding architectural decisions without owning day-to-day pipeline development • Own the vision and prioritization for customer-facing analytics and insight products (benchmarks, insight cards, modeled datasets, ML/AI features) • Partner with Product and Engineering to ensure these capabilities drive differentiation and customer value • Balance experimentation and innovation with delivery of durable, scalable data products • Lead and scale the analytics and ML organization; define roles, career paths, and team structure • Hire and develop senior talent who can operate autonomously and influence cross-functionally • Create clear operating rhythms, planning processes, and success metrics for the data organization • Foster a culture of accountability, curiosity, and outcome-driven execution • Own the data roadmap and prioritize initiatives based on business impact and strategic goals • Partner closely with Product, Engineering, GTM, Finance, and CS leadership to align on data priorities • Define and track data and analytics KPIs; ensure leadership has visibility into performance and outcomes • Guide vendor strategy and build-vs-buy decisions across analytics and ML tooling