UX Researcher, Personalization

Staff UX Researcher, Personalization

Hybrid - San Francisco, California

Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We're looking for a Staff UX Researcher to join our Design Research team and drive the user research agenda that supports trustworthy, personalized health guidance. This role will be laser focused on supporting the strategy for how we tailor insights, recommendations, and guidance to each member's physiology and goals in ways that feel accurate, explainable, and earned rather than presumptuous. You'll partner closely with Software Design, Product, Data Science, and Engineering, and you'll use rapid experimentation as a core research tool, not just a downstream validation step.

This is a hybrid-remote role, with the expectation to work from our San Francisco or Helsinki offices at least half-time.

• Own end-to-end research across generative, evaluative, and strategic studies to understand how members experience personalized biometric insights, including how they build or lose trust when recommendations are probabilistic, sensitive, or hard to verify and how they reconcile algorithmic data against their own felt experience.
• Design and run rapid experiments (A/B tests, multi-armed variants, staged rollouts) as a primary research tool for validating personalization changes, not solely as a post-hoc check on design decisions.
• Lead research into emerging, ambiguous problem spaces — particularly AI- and LLM-powered recommendation experiences — where established methods may need to be adapted or invented.
• Study how personalization should adapt across different member segments, health contexts, and levels of engagement, and where more personalization ceases to help and starts to feel presumptuous or invasive.
• Help define what "trustworthy" means operationally for Oura's personalization surfaces — transparency about how a recommendation was generated, appropriate hedging under uncertainty, and clear paths for members to correct or override the system.
• Embed research early in roadmap and planning conversations with Software Design, Product, and Data Science so personalization decisions are shaped by evidence from the start.

• Experience:
  
  8+ years of professional UX or design research experience, with meaningful work translating behavioral or usage data into qualitative research that changed a product roadmap.
• Research Expertise:
  Demonstrated ability to run both qualitative and quantitative research, including comfort with logs/behavioral data analysis and experiment design (A/B testing, statistical significance, sample sizing) — not just interviews and usability tests.
• Technical Acumen:
  Comfort reading behavioral analytics and data science output well enough to identify which human-observation method would explain an anomaly, and to speak credibly with data science partners about what a pattern does and doesn't tell you.
• Domain Awareness:
  Experience researching AI-driven or algorithmic features, with an eye toward explainability, trust, and appropriate confidence-setting.
• Problem-Solving: A strong point of view on translating emotionally complex findings — distrust, invalidation, feeling unseen — into concrete design principles teams can actually build against.
• Influence:
  Strong storytelling and stakeholder communication skills; able to influence product and design decisions without formal authority.
• Can-do attitude:
  You can operate independently across multiple concurrent research work streams, thrive in ambiguity, and build a research program that is respected…