• Partner cross functionally across Product to establish top-level KPIs, dashboards, and product roadmap planning • Define how success is measured for AI-powered product experiences, including adoption, engagement, quality, retention, and user outcomes • Guide the instrumentation of product data in collaboration with our Product Design, Product Management, and Engineering teams to enable reliable analysis of AI features and workflows • Design, evaluate, and interpret experiments to assess the impact of new AI capabilities and inform product decisions • Develop dbt models to transform and test our user behavior data in partnership with our Analytics Engineering team • Influence best practices for Product Analytics across teams and help define standards as the company scales • Contribute to defining the long-term vision and strategy for Product Analytics, balancing near-term needs with scalable, durable solutions

• Partner cross functionally across Product to establish top-level KPIs, dashboards, and product roadmap planning • Define how success is measured for AI-powered product experiences, including adoption, engagement, quality, retention, and user outcomes • Guide the instrumentation of product data in collaboration with our Product Design, Product Management, and Engineering teams to enable reliable analysis of AI features and workflows. • Design, evaluate, and interpret experiments to assess the impact of new AI capabilities and inform product decisions. • Develop dbt models to transform and test our user behavior data in partnership with our Analytics Engineering team • Influence best practices for Product Analytics across teams and help define standards as the company scales • Contribute to defining the long-term vision and strategy for Product Analytics, balancing near-term needs with scalable, durable solutions.

• Create confidence in product decisions by designing, analyzing, and communicating experiments that help teams understand what works and what doesn't. • Turn product data into strategic direction by identifying trends, customer behaviors, and opportunities that influence roadmap priorities. • Build a shared understanding of product health through dashboards and reporting that give Product and Engineering teams visibility into adoption, performance, and customer outcomes. • Help define how we measure success in an AI-first product by developing the metrics and evaluation frameworks that shape our agent-powered capabilities. • Bring data into the room early. Partner with Product Managers, Engineers, and Designers to frame problems, evaluate tradeoffs, and make better decisions before roadmaps are finalized. • Reveal what different customers need by using cohort analysis, segmentation, and behavioral data to uncover meaningful patterns and opportunities for improvement. • Bring clarity to ambiguity. Start with questions – not predefined reports – and determine what needs to be measured, analyzed, or built to help teams move forward with confidence.

• Analyse customer behaviour across key digital journeys to identify friction points, opportunities and changes in performance. • Translate behavioural data into simple, actionable recommendations for Product, UX, Experimentation and business stakeholders. • Combine quantitative and qualitative insights, including analytics, user research, voice of the customer, and session replay tools where available. • Help stakeholders understand the "why" behind performance by connecting customer behaviour, product changes and commercial outcomes. • Support teams in creating structured growth hypotheses based on data, customer insight and business priorities. • Work with Product Managers, UX, Engineering and business stakeholders to turn opportunities into experiment ideas, discovery questions or roadmap actions. • Support the design of A/B tests and other structured test-and-learn approaches. • Build, maintain and improve Airtable bases that support experimentation, product analytics, insight management and operational workflows. • Identify opportunities to reduce repetitive manual work through automation, low/no-code workflows and AI-supported processes.