Lead Product Manager - AI-Powered Learner Onboarding

Multiverse; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

27 days holiday

Private medical insurance

Gym membership

Wellbeing resources

Hybrid work

Work-from-anywhere

Job summary

United States Digital Space LLC is seeking a Lead Product Manager to own Prescribe, the product guiding learners to the right programme and their successful start. You will partner with Senior Engineering, design, data, and GTM teams in a London-based, hybrid role three days a week in the office.

You will own the conversion journey, drive experimentation, and shape AI-driven improvements that reduce time to commitment.

Qualifications

• Substantial experience as a PM with a track record of improving growth metrics.
• Ability to pull data, run cohort studies, and build dashboards.
• Experience designing and running rigorous A/B and multivariate experiments.
• Strong instincts for user experience and long-term strategy.
• Ability to align cross-functional teams without formal authority, including commercial, GTM and operations.
• Hands-on experience building products using AI/LLMs to generate or personalise content.

Responsibilities

• Own AI-native, conversational experiences that help learners and customers find the best programme.
• Define the journey from recommendation to committed learner and starting the programme.
• Collaborate with GTM, Operations and Data teams to improve attribution and funnel quality.
• Own conversion metrics, experiments roadmap, and guardrails for trustworthy AI.

Skills

PM experience

Data analysis

A/B testing

Cross-functional

AI features

PLG

UX focus

Job description

United States Digital Space LLC is seeking a Lead Product Manager to own Prescribe, the product guiding learners to the right programme and their successful start. You will partner with Senior Engineering, design, data, and GTM teams in a London-based, hybrid role three days a week in the office.

You will own the conversion journey, drive experimentation, and shape AI-driven improvements that reduce time to commitment.