• Define and execute the product strategy and roadmap for Payments, communicating products, innovations and business concepts to stakeholders. • Develop and articulate granular product and market requirements leveraging product management toolsets including Aha!, JIRA, and AI. • Collaborate with Engineering teams and external partners on functional design documents and project schedules. • Lead product performance reporting and analytics efforts leveraging tooling including Tableau, Pendo, and AI. • Present business updates to executives, senior leadership and stakeholders regularly. • Oversee new product launch activities, ensuring coordination across the company. • Engage with Customers and partners to gather product requirements and insights. • Conduct comprehensive market research and competitive landscape analysis. • Develop sales tools such as ROI calculators, collateral, video demos, battle cards, and more, and provide guidance on documentation and training materials to Education teams. • Present and demonstrate products at company conferences and events and in support of Sales efforts.

• Define and execute the product roadmap for the maintenance platform, including work order management, inspections, preventive maintenance, and resident communication • Partner with Operations, Engineering, and external vendors to translate business needs into scalable product solutions • Own end-to-end delivery—from requirements and prioritization through launch and iteration • Optimize workflows across key areas such as scheduling, technician productivity, and automated resident engagement • Drive integration strategy (e.g., PMS, CRM, middleware) to ensure seamless data flow and system interoperability • Leverage data and user feedback to continuously improve product performance and adoption • Support pilot programs and scale successful solutions across the portfolio • Identify opportunities to leverage AI to automate workflows (e.g., work order intake, routing, communication) • Partner with engineering on AI-enabled features such as recommendation engines, automation, and workflow optimization • Define success metrics and evaluate AI performance (accuracy, efficiency, user adoption) • Ensure responsible AI usage, including data quality, transparency, and operational reliability.

• Setting the vision: Define the one-year roadmap for the Data domain, look 3 to 6 months ahead to plan multi-squad projects, manage complex trade-offs, and set clear KPIs and OKRs. • Building our Data & AI foundation: Work on building our brand-new data warehouse as a robust data foundation, whilst owning the ongoing development of our AI infrastructure—including Chatbots and Agentic AI. • Enabling self-serve journeys: Help build self-serve data tools so colleagues across UW can get the insights they need at their fingertips. • Designing great features: Lead the design process for complex features and bridge the gap between multiple engineering teams to solve deep-seated user pain points. • Leading big deliveries: Manage the end-to-end delivery of large, multi-quarter initiatives, make high-stakes decisions (like feature deprecation or strategic pivots), and spot and manage any risks along the way. • Aligning stakeholders: Act as an Ambassador for the Data team. Keep a complex mix of internal and external partners on the same page, manage blockers proactively, and present clear, compelling strategic narratives to senior leadership. • Technical specs & integrations: Define complex, multi-system feature sets, design API integrations, and guide data modeling discussions with engineers to make sure our systems talk to each other seamlessly.

• Create and own a 2–3 year roadmap for Comet Planning. • Drive how we evolve from plant-specific manual interventions to an autonomous, network-wide optimization engine that handles massive scale and complexity. • Operate at the intersection of Engineering, Program Management, Design, and Physical Operations. • Build consensus among senior plant leaders and global fulfillment executives, translating deep technical constraints into clear, high-impact business outcomes. • Translate complex mathematical constraints (labor pools, machine changeovers, batching, and ganging logic) into scalable APIs and intuitive UI workflows (ScheduleCore). • Ensure that our digital "plan" is actually executable on the factory floor. • Ensure the planning engine handles diverse constraints like changeovers, labor pools, batching, ganging, and shipping SLAs. • Provide mentorship and direction to a small team of product managers, ensuring high-quality execution and strategic alignment. • Design feedback loops to measure how our planning decisions directly impact key manufacturing and shipping metrics.