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Lead Technical Product Manager

CompraTica Empleos

EMP:Management
London
Tiempo Completo
Remoto
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Numan    Founded in 2018, we’ve already grown to be a 300+ team distributed across the globe, united by a singular mission: empowering people to take control of their health.   Numan is transforming health: we’ve built a cutting-edge platform that integrates diagnostics, medication, supplements, digital programmes, and doctor consultations

Giving people the tools they need to maximise life.

  To deliver on our transformative mission, we are guided by our 5 company values:    • Patients first.

• Learn fast.

• Own the quality.

• Succeed together.

• Care deeply.

  Backed by top-tier investors, Numan is already having a positive impact on hundreds of thousands of patients here in the UK, and we want you to help us deliver this mission!The role:   This role is about taking our platform to the next level: moving toward sophisticated, predictive, and learning-based decisioning, with a clear path toward becoming a regulated medical device.

This is a senior, high-impact individual contributor (IC) role for someone who combines deep system understanding with clinical product judgement and real experience deploying AI/ML.

You are AI-enabled, well-resourced, and measure your success by what you ship and move, rather than the size of your team.

You move comfortably between high-level strategy and engineering-grade specifics.

You'll be: Lead the product direction and roadmap for the decision platform, from long-term strategy down to the detail of how a rule actually works.

Decide which features and capabilities create the most scalable value, balancing near-term execution with strategic bets.

Establish and systematically track the success metrics for the platform.

Set the direction for how the platform uses AI and machine learning, embedding predictive and supervised learning systems into production.

Build self-learning systems so the platform continuously improves on its historical recommendations while keeping safety and explainability central.

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