Staff UX Researcher, Personalization

<div class="content-intro"><p>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.</p> <p>Empowering the world starts with living <a href="https://ouraring.com/about-us">our values</a> 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.&nbsp;</p></div><p>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.</p> <p>This is a hybrid-remote role, with the expectation to work from our San Francisco or Helsinki offices at least half-time.</p> <h2>What You’ll Do</h2> <ul> <li>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.</li> <li>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.</li> <li>Lead research into emerging, ambiguous problem spaces — particularly AI- and LLM-powered recommendation experiences — where established methods may need to be adapted or invented.</li> <li>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.</li> <li>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.</li> <li>Embed research early in roadmap and planning conversation