Team Manager, Data Analytics & Business Intelligence
Listed on 2026-07-09
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IT/Tech
Data Analyst, Data Science Manager
Manager, Data Analytics & Business Intelligence
Location:
Hoboken - Hybrid
At Pearson, we are the world's digital learning company with more than 24,000 employees operating in 70 countries. We lead the education technology industry in design, service, and innovation. We are committed to bringing life to a lifetime of learning and to our talented team who make it all possible. By creating effective, engaging solutions, we provide boundless opportunities for learners at every stage of their journey around the world.
We achieve this through cutting-edge technology, uncompromising service, and high-quality products that are engaging and easy to use.
You will lead product analytics for Pearson's Higher Education courseware, integrations, and content authoring portfolio — products used by millions of students and tens of thousands of instructors. Your job is not to staff a reporting function. Your job is to make sure every product team in HE is making better decisions because of data: understanding how students and instructors actually use what we build, proving which bets pay off, and surfacing the opportunities our product managers couldn't see on their own.
You will manage a small team of product analysts and partner directly with Heads of Product, PMs, designers, engineers, and learning science. You report into the HE product organization, not into a central data function — because analytics here is a product capability, not a service desk.
What "good" looks like in this role
We expect strong product analytics leaders to drive five uses of data. You will lead your team and your product partners against all five:
Responsibilities
- Lead the product analytics team. Manage, coach, and grow a team of product analysts. Set the standard for analytical rigor, communication, and product partnership. Make every analyst on your team a stronger product thinker, not just a stronger SQL writer.
- Partner with product leadership on strategy. Sit in roadmap and quarterly planning. Bring the data point of view to prioritization. Push back when proposed work has no measurable outcome attached.
- Own the HE product KPI framework. Define the small set of metrics that matter — across commercial performance and learning outcomes — and make sure every team can see theirs in near-real time.
- Drive instrumentation and telemetry. Work with engineering and data platform teams to define what we measure, where, and how. Treat instrumentation as a first-class product requirement, not an afterthought.
- Lead and scale experimentation. Build the muscle, the tooling expectations, and the cultural norms for testing across HE products.
- Surface opportunities. Run regular discovery-oriented analyses across the portfolio. Bring forward "we should look at this" insights that change roadmaps.
- Communicate to executives.…
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