SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 147,900 - 203,000 / annual
Oura is seeking a Senior Machine Learning Data Scientist to join the Women's Health team. You will develop and commercialize cutting-edge machine learning models and algorithms leveraging wearable health data from Oura's award-winning Ring product to improve women's health outcomes.
Key responsibilities include:
- Develop and deploy advanced machine learning pipelines and models for innovative Women's Health features, with focus on time-series analysis and robust validation
- Drive commercialization of ML models and algorithms in collaboration with scientists, product managers, software developers, designers, and test engineers
- Design and execute rigorous statistical analyses for model performance evaluation, monitoring, and generating actionable insights to inform product strategy
- Conduct exploratory research to identify and characterize novel health sensing features, translating proof-of-concept ideas into scalable, commercialized products
- Contribute to development of best practices for machine learning within the Women's Health team
- Present and communicate complex technical concepts to diverse audiences
Oura's mission is to empower every person to own their inner potential through daily insights on readiness, activity, and sleep quality. The company has helped millions of people understand and improve their health.
Note: This is a remote US role with a preference for candidates based in San Francisco, San Diego, or Boston. Oura is not considering candidates residing in Alaska, Delaware, Iowa, Mississippi, Nebraska, South Dakota, West Virginia, or Wisconsin.
REQUIREMENTS:
- PhD in Biomedical Engineering, Electrical Engineering, Biostatistics, Computer Science, or 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 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
- Excellent communication skills and ability to articulate complex technical concepts to both technical and non-technical audiences
- Self-driven, motivated, pragmatic can-do attitude with delivery-focused mindset
NICE TO HAVE:
- Strong domain knowledge in Women's Health
- Experience with health data from wearables
