• Craft and champion a multi-year product strategy and roadmap for our Literacy/ELA product line. • Mentor and support your team, helping them develop strong product thinking and execution skills. • Partner closely with Engineering, UX, Marketing, and Sales to stay aligned on priorities and ensure smooth delivery. • Lead discovery to understand customer needs, market opportunities, and the competitive landscape. • Make smart decisions about where to invest based on customer impact, business value, and ROI. • Work with your team to turn strategy into clear, actionable team deliverables. • Monitor key metrics like adoption, revenue, and customer satisfaction — and use what you learn to inform next steps. • Contribute to annual planning, including budgets and resource needs. • Represent the Literacy/ELA product line in leadership conversations and serve as a thought leader internally and externally.

• Own a clearly defined area of the CMP product, with full accountability for the quality and direction of the backlog and the outcomes delivered within that area. • Before any initiative is committed to, define a clear outcome hypothesis and a measurement mechanism. • Maintain a well-prioritised, clearly articulated backlog. User stories define the problem and desired outcome, not the solution. Solution design belongs with the engineering team. • Own the instrumentation requirements for every feature shipped. Acceptance criteria must include what needs to be tracked and how success will be measured. • Lead all squad ceremonies: stand-ups, sprint planning, backlog grooming, and retrospectives. • Own direct relationships with customers within your product area. Do not rely on Customer Success to proxy the customer voice. Own the relationship directly. • Participate in structured customer conversations as part of the Product Trio (Product Owner, UX Designer, and Engineer). • Bring proposals grounded in customer insight and data. Proposals come from direct customer discovery sessions, not internal assumptions or stakeholder opinions. • Engage with the underlying problem, not the surface request. When feedback arrives, probe for the root cause before forming a view on what to build. • Every initiative proceeds with a defined outcome hypothesis. What does success look like? How will it be measured? • Track whether outcomes have actually been reached after delivery. Feature adoption is not enough. Confirm whether the expected customer behaviour or business outcome materialised. • When engineering, UX, and stakeholders have competing views, the Product Owner makes the call. Decisions are made with the available evidence, the rationale is documented, and the outcome is owned. • Use AI tools to accelerate research, synthesis, documentation, and analysis. Reinvest that time in the decisions and relationships that require human judgement. • Own and manage roadmap candidates for your product area. Contribute well-evidenced, outcome-defined candidates to quarterly planning cycles. • Receive and evaluate inbound requests from Customer Success and commercial teams. Assess them against the evidence bar. Where requests have merit, shape them into properly defined initiatives for quarterly planning, not ad-hoc additions to the sprint. • Keep Customer Success and Product Marketing informed of progress, upcoming releases, and what is not coming. No should always come with a reason. • Own the handoff to Technical Writing ahead of every release. Documentation should be ready at the point features ship.

• Drive growth across a portfolio of web products, focusing on maximizing ARPU and conversion rate. • Own the design and execution of a science-backed experimentation program. • Optimize conversion funnels end to end: acquisition → paywall → revenue retention. • Define, prioritize, and run high-impact growth experiments across multiple products. • Improve churn-prevention flows and apply statistical rigor to experiments. • Collaborate with design, engineering, and data teams to implement A/B tests.

• Experience delivering AI-powered product features and working within teams that leverage AI-assisted development (e.g. LLM tooling, automation) to improve delivery and product outcomes • Strong AI fluency, including a practical understanding of machine learning, generative AI, and data-driven product design • Experience partnering with engineering teams building AI/ML-powered solutions • Understanding of core AI concepts (e.g. model performance, accuracy, bias, and limitations) and their impact on product design and user experience • Develop and maintain a deep understanding of customer needs, market trends, and business goals • Work closely with various stakeholders across multiple time-zones in engineering, design, marketing, commercial, and customer success • Conduct customer interviews, surveys, and market research • Define and prioritize product requirements • Oversee the entire product development lifecycle • Identify upcoming risks and proactively implement strategies to mitigate them, ensuring successful product delivery • Together with the Technical Product Manager, make trade-off decisions when faced with conflicting priorities, resource constraints, or technical limitations • Collaborate with engineering and design teams to shape solutions that are scalable, feasible, and aligned to customer and business needs • Drive prioritization, trade-offs, and decision-making across stakeholders • Plan and execute successful product launches • Analyze data and metrics to measure performance • Use data and metrics to inform product strategy and continuous improvement • Foster strong documentation, knowledge sharing, and clear product communication