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Portfolio Lead at Multiverse

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Jack & Jill
Full Time position
Listed on 2026-06-22
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Job Title

Portfolio Lead

Salary

Not Disclosed

Company Description

Multiverse.io is a Series D-funded edtech leader backed by Bessemer Venture Partners, reinventing professional development by replacing traditional degrees with high-impact apprenticeships in data, engineering, and business.

Job Description

As Portfolio Lead for the Data vertical, you will own the product roadmap for UK data upskilling apprenticeships. You’ll blend technical expertise with strategic product management to define curriculum excellence, support complex GTM deals, and ensure Multiverse.io products remain at the cutting edge of the modern data stack for global clients.

Location

London, UK

Why this role is remarkable
  • Shape the future of education by replacing outdated degree models with a modern, applied learning curriculum that directly impacts the careers of thousands of learners.
  • Join a high-growth, Series D scale-up backed by world-class investors like Bessemer Venture Partners, operating at massive scale across the UK.
  • Work at the intersection of product strategy and technical data domains, influencing how the world's leading organizations build their data science and AI capabilities.
What You Will Do
  • Own the strategic roadmap and performance metrics for the Data product set, identifying new UK releases to drive bookings and improve learner retention.
  • Serve as the technical domain expert for Go-To-Market discovery, aligning data products with the needs of Chief Data Officers at major enterprises.
  • Collaborate with Learning and Technology squads to quality-assure synchronous and blended learning models, ensuring high engagement and technical relevance for the modern stack.
The ideal candidate
  • Brings deep domain expertise in data science, analytics, or engineering, with a strong grasp of the modern data stack including data lakes, warehouses, and ML libraries.
  • Has a proven track record of launching and iterating on technical products or curricula in a fast-paced, cross-functional environment.
  • Exhibits exceptional communication skills, capable of translating complex technical specifications for stakeholders ranging from junior learners to C-suite executives.
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