• Partner with Applied ML engineers to define the requirements for discovery and ranking algorithms. • Identify and prioritize the data signals (user intent, historical behavior, market urgency) that will improve model accuracy and conversion. • Establish KPIs for ensuring that the roadmap translates directly into business growth. • Act as the Product Owner for our internal experimentation tools. • Define the technical requirements for automated triggering, variance reduction, and real-time result calculation. • Collaborate with Engineering to design and enforce a robust event-tracking schema. • Manage the lifecycle of data products from ingestion and dbt transformation to final consumption in the app or ML models. • Serve as the technical translator between the Data/ML teams and the core Product, Design, and Engineering (PDE) squads. • Lead the evaluation of third-party technical vendors (CDPs, ML Ops tools, Analytics stacks) vs. building proprietary in-house solutions. • Work with the XFN Stakeholders to ensure the technical data roadmap is synced with other teams.