Product Management

Data PM– Job Description

Why Pearson?

Join the world’s leading learning company on a mission to help millions unlock their potential. On our Pearson+ team, data isn’t just numbers—it’s the fuel that powers strategic decisions. Here, your insights will directly shape sales and marketing efforts, roadmap investments, pricing, and channel strategies that drive revenue growth and improve learner outcomes.

Key Responsibilities

1. Data Strategy & Product Lifecycle Ownership

• Act as the data PM owner across the full product lifecycle: kickoff, sprint planning, experimentation, release, and post-launch analysis

• Partner with analytics teams and maintain single source of truth for KPIs, metric definitions, and event taxonomy

• Ensure data readiness for all releases (instrumentation, QA, experiment design, reporting)

• Serve as a partner for Product, Marketing, Finance, Engineering, Analytics teams

2. KPI Frameworks, Instrumentation & Data Quality

• Design self-service dashboards for real-time KPI monitoring

• Partner to define north star metrics, funnels, and leading indicators across acquisition, engagement, and monetization

• Own event tracking design (e.g., Mixpanel, clickstream) and ensure consistency across platforms

• Define requirements for QA processes to ensure accuracy of dashboards and experiment results, collaborate on ETL and data-quality initiatives.

3. Experimentation & Growth Optimization

• Partner with Product to Define and operationalize A/B testing frameworks, including success metrics, segmentation, and guardrails

• Analyze experiment results and translate into clear product and business decisions

4. Forecasting, Revenue Modeling & Strategic Insights

• Build and maintain financial models to test pricing, bundling, channel mix scenarios, and “what-if” scenarios to recommend adjustments

• Evaluate sales metrics, ASP trends, and pricing strategies

• Identify growth opportunities through funnel analysis, cohort behavior, and LTV insights. As a result, will Influence roadmap prioritization and growth levers

5. Insights, Storytelling & Senior leadership Influence

• Present analyses to senior leadership, ensuring clarity for non-technical audiences

• Create with analytics teams executive-ready dashboards and reports focused on business impact in service of the Pearson+ product

• Define automations for weekly/monthly reports to keep stakeholders aligned

• Translate data into insights and concise business recommendations

6. AI / LLM-Driven Analytics & Automation

• Leverage LLMs (e.g., Cursor, Claude, internal AI tools) to automate insight generation and anomaly detection

• Define use cases for AI-powered analytics (e.g., auto-generated dashboards, self-serve insights and processes)

What We’re Looking For

Required

• 5+ years in product analytics, business analytics, ideally in SaaS, e-commerce, subscription, or EdTech.

• Bachelor’s in Business, Finance, Economics, industrial engineering, Data Science or related field (or equivalent experience).

• Proven experience owning metrics, instrumentation, and experimentation frameworks end-to-end

• Strong SQL proficiency (ability to explore and validate data independently;)

• Experience with tools like Mixpanel, Tableau, Snowflake (or similar stack)

• Strong business/finance acumen— comfortable with P&L concepts

• Excellent storytelling—ability to simplify complex data ability and translate data insights into clear business decisions

• Familiarity with LLM tools and AI-assisted analytics workflows

Behavioral Expectations

• Customer-Centric Thinking

• Ownership & Accountability, Strategic Influence and Collaboration

• Raising the Bar: Drive excellence in data quality, experimentation and insight depth

• Innovation Mindset: Continuously identify opportunities to leverage AI and automation

What You’ll Gain

• High Visibility: Your recommendations will steer multimillion-dollar decisions

• Growth & Learning: Access to industry-leading L&D resources, mentorship from senior leaders, and exposure to cross-disciplinary projects.

• Collaborative Culture: A supportive, global, and diverse team that values data fluency, creativity, and continuous improvement.

• End-to-End Ownership: Influence from instrumentation → insight → business outcome

Ready to influence strategy and execution at scale? Apply now and help shape the future of learning at Pearson.

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