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Salary: USD 147,900 - 203,000 / annual
Oura is seeking a Senior Machine Learning Data Scientist to join its Women's Health team. The role focuses on developing and commercializing cutting-edge machine learning models and algorithms that leverage wearable health data to improve women's health outcomes.
Key Responsibilities:
- Develop and deploy advanced machine learning pipelines and models for innovative Women's Health features, with emphasis on time-series analysis and robust validation.
- Drive commercialization of ML models and algorithms, collaborating 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 decisions.
- Conduct exploratory research to identify and characterize novel health sensing features, translating proof-of-concept ideas into scalable, commercialized products.
- Contribute to developing best practices for machine learning within the Women's Health team.
- Present and communicate complex technical concepts to diverse audiences.
- Lead complex projects and mentor junior team members.
This is a remote US role with a preference for candidates based in San Francisco, San Diego, or Boston.
Requirements:
- PhD in Biomedical Engineering, Electrical Engineering, Biostatistics, Computer Science, or related field.
- 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 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.
