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Staff Machine Learning Data Scientist at Oura. At Oura, our mission is to empower every person to own their inner potential. With our award-winning Oura Ring and app, we help over 2.5 million people turn insights about sleep, activity, and readiness into healthier, more balanced lives. We believe that starts from within — by creating a culture where our team feels supported, included, and inspired to do their best work. . Our values. guide how we show up for each other and our community every day.. We are looking for a . Staff Machine Learning Data Scientist . to join our Science team. This high-impact role will focus on building robust, scalable, and accurate physiological machine learning models from large-scale wearable and health datasets. You’ll work closely with cross-functional partners across product, software engineering, and testing teams to develop the next generation of Oura's health insights.. This is a remote US role with a slight preference for candidates based on the East Coast. . We have offices in San Francisco and San Diego for those who prefer hybrid or office settings. Oura employees in other major cities (like Boston and New York) occasionally gather informally at local co-working locations.. What you will do: . . Design and develop scalable data generation pipelines that prioritize robustness, reproducibility, and quality across diverse physiological signals.. . Research, prototype, and implement novel ML architectures for large-scale time-series modeling of health and physiological data.. . Build scalable training pipelines to support high-throughput model development and iteration.. . Design comprehensive evaluation strategies for model performance and clinical validity.. . Collaborate cross-functionally with engineering, product, and validation teams to bring scientific models to production.. . Plan and support long-term roadmap and mentor junior team members on best practices in modeling and deployment.. . We would love to have you on our team if you have:. . Have a PhD in machine learning, artificial intelligence, biomedical engineering, or a closely related field.. . Bring 5+ years of relevant industry experience (post-PhD) working with applied ML in a product setting.. . Have hands-on experience developing and deploying large time-series models, especially those built on sequential physiological or wearable data.. . Demonstrate strong programming skills in Python and experience with cloud-based ML (e.g., AWS, Github, Pytorch, Docker).. . Possess a deep understanding of scalable ML workflows, including data pipelines, evaluation frameworks, and deployment to production.. . Self-starter and vision-driven with strong collaboration and communication skills and thrive in cross-functional settings.. . (Bonus) Have a background in physiology, health sensing, or digital biomarkers.. . (Bonus) Have experience shipping ML models in production environments and conducting real-world validation.. . Company Location: United States.