Shape the vision and strategy for member understanding & intelligence: Define and evolve a product vision for how Oura understands members and serves members truly personalized experiences. Build conviction around which context types unlock the most member value and business impact, balancing platform capabilities with member-facing experiences.
Own outcomes across both platform and member experience layers: Drive a roadmap that balances robust platform capabilities (APIs, data models) with delightful member-facing features. Navigate the tension between building infrastructure that enables other teams and shipping features that prove member value.
Deeply understand our members and their health journeys: Partner with research, science, and data teams to understand which contextual factors actually drive personalization quality and health outcomes. Map end-to-end journeys, identify where generic guidance fails members, and prioritize the context types that matter most for our target ICPs and health outcomes.
Partner with senior and executive leaders: Structure clear narratives and options for high-impact decisions in a high-ambiguity environment. Connect work to company-level goals and use measurable outcomes to build trust and alignment across Oura.
Drive internal adoption of capabilities: Work closely with other product teams to identify the highest-value integration points. Ensure the platform is well-documented, understood, and reliably supports their roadmaps.
Define success metrics, instrumentation needs, and experimentation plans for Context Engines. Build the A/B testing infrastructure that enables rapid iteration on personalization approaches. Use data and member feedback to validate which context types drive member value.

Requirements

7+ years of Product Management experience in data platform, ML, or consumer technology products, with a proven track record of shipping successful products at scale. At least 2 years at Staff/Principal level or equivalent strategic scope.
You have shipped ML-powered personalization or LLM features in production. Hands-on experience with prompt engineering, RAG architectures, and managing cost/performance tradeoffs of AI at scale. You understand constraints of shipping GenAI at scale, and lead technical roadmap discussions on model integration, experimentation infrastructure, and vendor selection.
Experience shipping consumer-facing features at scale. You understand the "Value > Effort" equation and can balance platform capabilities with member-facing experiences that feel rewarding, not burdensome.
Ability to design data architectures and ontologies that scale across multiple use cases and teams. Comfortable working with concepts like ETL pipelines, data normalization, and interoperability standards.

Benefits

Competitive salary and equity packages
Health, dental, vision insurance, and mental health resources
An Oura Ring of your own plus employee discounts for friends & family
20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
Paid sick leave and parental leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Product ManagementMachine LearningPersonalizationPrompt EngineeringRAG ArchitecturesA/B TestingData ArchitectureETL PipelinesData NormalizationInteroperability Standards

Soft Skills

Strategic ThinkingCollaborationCommunicationDecision MakingProblem SolvingAdaptabilityTrust BuildingAlignmentNarrative StructuringHigh-Ambiguity Navigation