Multiverse is the upskilling platform for AI and Tech adoption.

We have partnered with 1,500+ companies to deliver a new kind of learning that’s transforming today’s workforce.

Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.

In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.

But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.

Join Multiverse and power our mission to equip the workforce to win in the AI era.

What we need

As an Analytics Product Owner, you will design, build and manage analytics products that serve teams across the business – shaping how commercial, operations and learner outcomes decisions get made. We expect you to work with significant autonomy, owning product roadmaps end-to-end and serving as the go-to resource for your teammates on both tooling and domain questions.

The role sits within the Data & Insight team, reporting to the Director of Data Products. You will be collaborative and user-centric, with a bias for action and a high bar for quality.

What you’ll focus on

Product ownership

– Independently scoping and prioritising roadmaps for analytics products, translating complex stakeholder needs into clear feature requirements and delivery plans

– Driving end-to-end delivery of substantial product initiatives, making trade-off decisions between scope, quality and timeline while managing dependencies across multiple teams

– Establishing product success metrics and feedback loops, using usage data and stakeholder input to iteratively refine features and guide future product direction

Analytics design and build

– Designing end-to-end data product architectures that balance technical constraints with user needs, making tooling decisions that optimise for maintainability and team capabilities

– Identifying architectural bottlenecks in existing analytics systems and driving implementation of scalable solutions that become reference patterns for the team

– Translating ambiguous stakeholder requirements into concrete data models and visualisation frameworks, establishing design standards that new team members adopt

Technical expertise

– Demonstrating deep expertise in core analytics tools (Tableau, Metabase, SQL) and actively evaluating emerging AI and build tools to solve team problems with minimal guidance

– Acting as the go-to resource for teammates on core tooling, and driving adoption of new technologies by building proof-of-concepts with a clear articulation of business value

Domain and data knowledge

– Serving as the go-to expert for specific data domains — able to explain complex data structures, lineage and business context to both technical and non-technical stakeholders

– Identifying data gaps and quality issues that impact product decisions, proactively proposing solutions and driving remediation across multiple teams

– Translating business problems into data requirements by deeply understanding how domain data flows through systems and influences key business processes and metrics

Stakeholder engagement

– Proactively identifying and engaging the right stakeholders across multiple teams to shape product roadmaps that balance competing business priorities

– Translating complex technical constraints and opportunities into clear business value propositions that secure buy-in from senior stakeholders

What we’re looking for

Required

– Demonstrated ability to work autonomously across the full data product lifecycle – from discovery and scoping through to delivery and iteration

– Deep expertise in Tableau and SQL, with a track record of 2+ years of high-quality analytics deliverables

– Strong product instincts: comfortable making trade-offs between scope, quality and timeline without needing close direction

– Ability to translate complex stakeholder needs into structured product requirements and delivery plans

– Experience identifying and driving improvements to analytics architecture or tooling, not just executing against defined briefs

– Meticulous attention to detail

– Commitment to Multiverse’s mission and values

Desirable

– Experience evaluating and adopting emerging tools – inc AI-powered platforms (e.g. Retool, Replit)

– Familiarity with semantic layers (e.g. Cube)

– Working knowledge of the education or skills sectors

Benefits

– Time off – 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend)