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Machine Learning Data Scientist

ŌURA

ŌURA

Software Engineering, Data Science
San Francisco, CA, USA
Posted on Sep 16, 2024

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 2.5 million 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 have offices in San Francisco and San Diego for those who prefer hybrid or office settings and employee hubs, including New York City, Boston, Los Angeles, Seattle, and more.

We are looking for a Machine Learning Data Scientist to join us to build our next-gen machine learning algorithms. You will be one of the key team members developing new exciting sensing capacities and user-facing features for Oura’s next-gen products.

What you will do:

  • Contribute to the research, development and deployment of signal processing and machine learning algorithms for Oura features/products.
  • Conduct early stage exploratory research to identify and characterize new potential sensing features and functionality. Develop proof-of-concept features and work with a cross-functional team to take these from POC to a commercialized product.
  • Design and support internal and external data collection studies to develop, evaluate, benchmark and improve new biomarkers and algorithms.
  • Document, summarize, and present data analysis and algorithm performance results with concrete actionable recommendations for a broad audience on a regular basis.
  • Coordinate with cross-functional teams and overseas stakeholders.

This is a remote US role with a slight preference for candidates based on the East Coast.