Staff Applied Machine Learning Scientist (Health)
Core
Design, develop, and validate machine learning and statistical methods for health features using wearable physiological and behavioral data to expand WHOOP's health sensing capabilities.
Role type
Staff Applied Machine Learning Scientist (Health)
Builds
Health sensing features and algorithms for wearable devices
Domain
Digital Health / Wearables / Time-series analysis
Deliverable
production ML models
Required skills
Applied algorithm and statistical craft, Time-series and longitudinal data modeling, Wearable/physiological signal processing (PPG, IMU, HR/HRV), Study design and evaluation protocols, Python (NumPy, SciPy, pandas, scikit-learn, PyTorch/TensorFlow), Cross-functional leadership
Preferred skills
None stated
Technologies
NumPy, SciPy, pandas, scikit-learn, PyTorch, TensorFlow
Responsibilities
Lead design, development, and validation of ML methods for health features; Frame ambiguous health questions into well-scoped modeling problems; Set methodological and quality standards for the health domain; Develop approaches for time-series and multimodal data; Partner with ML Engineers to translate methods into production systems; Serve as technical counterpart to Product and Digital Health partners; Mentor scientists and engineers
Seniority
Staff, hands-on IC with leadership
