Staff Applied Machine Learning Scientist (Health)

What you'll do

• Lead the design, development, and validation of ML and statistical methods for Health features.
• Turn ambiguous health and product questions into studies or modeling plans with clear evaluation criteria and honest treatment of uncertainty.
• Set domain-wide methodological standards and partner with engineering, Product, and clinical and Digital Health teams to support production and evidence quality.

What they ask for

• Master's or PhD (or equivalent professional experience) in a related quantitative or health-science field.
• 7+ years of professional experience developing algorithms, applied ML models, or statistically rigorous analyses in health, wearables, medical devices, digital health, or a closely related domain.
• Demonstrated Staff-level technical leadership, including setting reusable standards, influencing multi-team outcomes, mentoring senior ICs, and prioritizing under uncertainty.
• Strong statistics and ML foundation for time-series and longitudinal data; experience with physiological signals or an adjacent time-series domain; end-to-end study or evaluation design; and strong Python skills.

Pay

$170K – $230K USD base salary

Tools

Python, NumPy/SciPy/pandas, scikit-learn, PyTorch/TensorFlow, PPG, IMU, HR/HRV

AI focus

Applied machine learning and statistical analysis for health features using wearable physiological, behavioral, and related member data.