Senior ML Data Scientist, Health Sensing

Our mission at Oura 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. 

This is a remote US role with a preference for candidates based in San Francisco, San Diego, or Boston. 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.

We are seeking a highly experienced and driven Senior Machine Learning Data Scientist to join our health sensing team. You will play a pivotal role in developing and commercializing cutting-edge machine learning models and algorithms, leveraging wearable health data to help members detect and understand illness. This role carries a high degree of independence — you will own projects end to end, set your own technical direction, and partner directly with product and engineering to bring your work to members.

• →Contribute to the development and deployment of advanced machine learning pipelines and models for innovative illness detection features, focusing on time-series analysis and robust validation.
• →Drive the commercialization of machine learning models and algorithms, collaborating closely with cross-functional teams including scientists, product managers, software developers, product designers and test engineers, serving as the primary science partner for illness algorithm work.
• →Design and execute rigorous statistical analyses for model performance evaluation, monitoring, and generating actionable insights to inform strategic product decisions.
• →Independently scope and conduct in-depth exploratory research to identify and characterize novel health sensing features, translating proof-of-concept ideas into scalable, commercialized products.
• →Identify and prioritize the highest-impact opportunities in a broad problem space, and drive them from open question to shipped capability with limited direction.
• →Monitor and improve the performance of algorithms already running in production at scale, using large-scale member data to guide where to invest next.
• →Present and communicate complex technical concepts to diverse audiences.

• PhD in Biomedical Engineering, Electrical Engineering, Biostatistics, Computer Science, or a related field, plus 3+ years of industry experience in machine learning and data science.
• 5+ years of advanced programming experience in Python and SQL.
• Extensive experience with a wide range of machine learning and statistical modeling techniques, including deep learning, time-series analysis, and signal processing.  
• Demonstrated experience in the full lifecycle of developing and commercializing machine learning models and algorithms.
• Proven ability to operate independently: comfortable being the sole scientist on a project, defining your own roadmap, and unblocking yourself without waiting for direction. You move quickly and prioritize effectively.
• Excellent communication skills, and the ability to articulate complex technical concepts to both technical and non-technical audiences.
• Domain knowledge in illness, infection, or immune response physiology, and experience with health data from wearables are significant pluses.