Oura is looking to solve the business and technical problem of providing advanced, high-impact features for athletes and highly active members seeking to optimize their physical performance by moving beyond foundational tracking to provide actionable coaching and personalized insights.
Requirements
- Deep, hands-on experience working with time-series data from a multi-axis accelerometer, gyroscope, or similar MEMS sensors (preferably in the consumer wearable or biomechanics space).
- Expert-level proficiency in Python, including deep knowledge of scientific/ML libraries, and experience building robust, scalable, and production-ready code.
- Strong, hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
- Expert-level proficiency in SQL and data wrangling, and comfort contributing to and maintaining the data pipelines for the features you develop.
- A deep, intuitive understanding of experimental design, causal inference, and validation methodologies for ML-powered product features.
- Familiarity with end-to-end development using AWS (or a similar cloud service).
- Experience with MLOps principles and tools for model deployment and monitoring.
Responsibilities
- Lead the end-to-end research, prototyping, and development of novel algorithms for advanced activity analysis, with an initial focus on running dynamics and advanced activity metrics.
- Design, build, and deploy production-grade ML models that translate complex sensor data into personalized, actionable insights for Oura members.
- Take full ownership of projects from initial data exploration and signal processing through to robust validation, deployment, and post-launch monitoring and iteration.
- Partner closely with Product, Engineering, and Design to define the technical vision and roadmap for the Performance squad, ensuring our work is scientifically rigorous and delivers tangible member value.
- Act as a technical leader and mentor for other data scientists, sharing your expertise and helping to elevate the team's best practices in signal processing, machine learning, and code quality.
Other
- 6+ years of relevant work experience (including deployment to production) as a data scientist or machine learning engineer, with a track record of leading complex projects.
- Experience working with international and distributed teams.
- Prior experience in the athletic performance technology space.
- A background in biomechanics, kinesiology, or sports science.
- Experience with embedded systems/firmware development.
