> Markdown version of [/jobs/ext/2545805-lead-data-analytics-business-intelligence](https://www.wearedevelopers.com/jobs/ext/2545805-lead-data-analytics-business-intelligence). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead, Data Analytics & Business Intelligence - **Company:** Pearson - **Location:** Hoboken, NJ, United States (Remote available) - **Experience:** Expert - **Salary:** $185,000.0 - $215,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, BigQuery, Data Infrastructure, Data Systems, Python (Programming Language), Mixpanel, SQL Databases, Tableau (Software), Usage Analysis, Snowflake - **Published:** August 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=8ace4084a60d951a ## About the Role * 8+ years in product analytics, with at least 2-3 years managing analysts. You've done the work and you've built the people who do the work. * Proven track record delivering complex data solutions and measurable business impact. You can point to decisions, experiments, roadmap changes, or product improvements that happened because of analysis you led. * Experience partnering with business leaders and managing cross-functional projects. You know how to work across product, engineering, design, data, and commercial stakeholders to move from insight to action. * Fluency in the product operating model. You've worked directly with empowered product teams (or you've helped create them) and you understand the difference between feature teams and product teams. * Strong experimentation chops. You can design a test, size it, read it, and tell a PM when not to run one. * Technical depth: SQL (BigQuery, Snowflake), product analytics tools (Mixpanel or equivalent), Tableau, Python a plus. We expect you to be hands-on - you should still be able to run the analysis yourself, even when you don't have to. * Sharp communication. You can hold your own in a room of senior product and engineering leaders and translate ambiguity into clear questions and clearer answers. * Strongly preferred: experience in education, edtech, or any domain where learning, behavior change, or skill acquisition is the core user outcome. You should care that what we build actually improves learning outcomes. ## Description Description: This role aligns to Industry Level Titles such as Product Analytics Director, or Senior Manager of Product Analytics., Success in this role means setting the product analytics vision for HE and making data a practical, trusted driver of product strategy, commercial outcomes, and learning outcomes. You will lead your team and partners against these expectations: * Understand actual behavior. Instrument products so we can see what students and instructors do , not what they say . Close the gap between stated needs and revealed behavior. * Measure business and learning performance. Define and own the KPI trees for HE products - both commercial (activation, retention, revenue per learner) and learning (engagement-to-outcome conversion, time-on-task efficiency, assignment completion, demonstrable mastery gains). At Pearson, a product that drives revenue but not learning outcomes is a failure. Your metrics must reflect both. * Prove which ideas work. Stand up and scale the experimentation practice across HE - A/B tests, holdouts, live-data prototypes. Coach PMs on test design, sample sizing, and reading results honestly (including the unwelcome ones). Kill bad ideas faster. * Inform product decisions. Replace opinion-driven debates with evidence. When leadership, PMs, or stakeholders disagree, you produce the analysis that resolves the question - or makes clear the question can't be resolved with the data we have, and what we'd need to collect. * Inspire new product opportunities. Mine our data - usage, outcomes, support, content interaction, instructor behavior - to surface opportunities no one asked you for. Some of the most valuable product work in this org should be initiated by your team, not handed to it. * Raise the bar for the analytics function. Coach and lead analysts while fostering innovation, analytical rigor, continuous improvement, and strong product partnership., * Lead the product analytics team. Manage, mentor, and grow a team of product analysts. Set the standard for analytical rigor, communication, and product partnership. M * Drive departmental vision and strategy. Align analytics priorities with HE product goals, business strategy, and measurable learning and commercial outcomes. * Partner with product leadership on strategy. Sit in roadmap and quarterly planning, bring the data point of view to prioritization, and push back when proposed work has no measurable outcome attached. * Build and sustain cross-functional partnerships. Work closely with product, design, engineering, learning science, and data platform partners to maximize the impact of data across the portfolio. * Own the HE product KPI framework. Define the small set of metrics that matter across commercial performance and learning outcomes, and make sure teams can see and use them in near-real time. * Drive instrumentation and telemetry. Partner with engineering and data platform teams to define what we measure, where, and how, treating instrumentation as a first-class product requirement. * Lead and scale experimentation. Build the best tooling, expectations, and cultural norms for testing, evidence-based decisions, and honest interpretation of results across HE products. * Surface new product opportunities. Run discovery-oriented analyses across usage, outcomes, support, content interaction, and instructor behavior to identify opportunities that can change roadmaps. * Communicate insights to executives. Translate complex analysis into clear, actionable narratives that HE and Pearson leadership can use to make decisions. * Govern data quality. Maintain definitions, lineage, and trustworthiness so analytics outputs are reliable and decision-ready. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Making Data Warehouses fast. 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