• Own end-to-end product delivery for bespoke AI engagements — from requirements definition through go-live and iteration • Drive scope discovery and gap analysis • Translate complex business problems into structured, testable AI solution designs • Define and maintain solution roadmaps • Lead discovery sessions, stakeholder workshops, and solution alignment meetings with VP- and C-suite client contacts

• Design and execute a platform roadmap for insight capabilities that address real customer needs, leveraging data from Renaissance's educational assets (assessments, skill practice, reading activities, and instruction) • Lead the software development lifecycle from discovery to launch, translating high-level launch goals and initiatives into tactical integration plans to reach those goals. • Collaborate and influence stakeholders across the organization on data-driven initiatives that support broader company strategy • Work closely with 1-2 engineering teams to execute roadmap deliverables • Apply generative AI tools and stay current with industry trends to solve user challenges and maintain competitive advantage • Use strong analytical skills to interpret data, inform priorities, and drive enhancements that deliver measurable business and user value • Champion data governance best practices and ensure ethical AI principles guide product development • Collaborate closely with engineering leadership to define product requirements and release criteria • Partner with marketing and solution teams to develop product positioning and communicate key benefits

• Discover real business problems • Design product solutions • Write deep specifications using AI • Prototype products yourself • Work with engineers for complex builds • Drive adoption — a top priority of this role

• As a PM I, you will be responsible for the Artificial Intelligence and Data journey within the RGM and Demand platform. Your focus will be to ensure that Traditional AI and GenAI capabilities are not only developed but effectively adopted and understood by end users in Sell-in and Sell-out operations. • AI Journey Leadership: Map and develop the user experience across all interactions with artificial intelligence in GPLAN (from demand forecasts to scenario simulations with GenAI), ensuring the technology addresses real pain points in the planning process. • Explainability and Trust (Explainable AI): Operate at the intersection of Data Science, Design (UX) and Business teams. You will be responsible for ensuring users understand the reasoning behind algorithmic recommendations, reducing bias from manual intervention (unjustified adjustments to the machine forecast). • Model Lifecycle Management in the Product: Define the scope of AI deliveries in MVP format. You will need to balance the complexity of data models with delivery timelines, deciding when to use simple heuristics and when to apply advanced predictive models. • AI Adoption and Performance Metrics: Establish and monitor data-journey-specific indicators, such as recommendation acceptance rate, improvement in WAPE (forecast error), bias, and reduction in planning cycle time. • Alignment with Technical and Business Stakeholders: Negotiate priorities directly with Machine Learning Engineers and Data Scientists, translating planners’ needs into technical requirements and vice versa.