Role Summary
We are looking for a Biometric Data Scientist to design and deploy the core intelligence engine for our wearable platform. You will be responsible for translating raw sensor streams (PPG optical heart rate, R-R intervals, accelerometry, and skin temperature) into actionable, validated physiological scores—including Daily Strain, Nervous System Recovery, and Sleep Stage Classification.
Key Responsibilities
- Algorithm Development: Design mathematical and machine learning models to calculate Heart Rate Variability (HRV - RMSSD/SDNN), Resting Heart Rate (RHR), cardiovascular Strain, and Sleep Architecture (Light, Deep, REM, Awake).
- Signal Processing & Noise Filtering: Develop digital filters to detect and remove motion artifacts caused by movement during workouts or restless sleep using multi-axis accelerometer fusion.
- Biometric Calibration: Establish personalized rolling baselines (e.g., 14 to 30-day moving averages) to normalize scores based on individual user physiology.
- Validation & Benchmarking: Validate proprietary algorithms against clinical ground-truth devices (e.g., Polysomnography for sleep, ECG/Holter monitors for HRV).
- Production Deployment: Convert prototype Python/R algorithms into optimized, production-ready modules (or C++/C bindings) for execution in cloud services or mobile edge pipelines.
Required Technical Stack & Qualifications
- Education: M.S. or Ph.D. in Biomedical Engineering, Computational Neuroscience, Signal Processing, Data Science, or a related quantitative field.
- Signal Processing: Deep expertise with digital signal processing (DSP), time-frequency analysis, Butterworth/Kalman filtering, and PPG/ECG waveform processing.
- Languages & Tools: High proficiency in Python (NumPy, SciPy, Pandas, scikit-learn, PyTorch or TensorFlow) and SQL.
- Domain Knowledge: Expert understanding of autonomic nervous system dynamics, cardiovascular response to physical exertion, and circadian rhythm science.
Preferred Experience
- Prior experience working specifically with wearable sensor data (smartwatches, chest straps, or smart rings).
- Familiarity with clinical health data standards and medical device algorithm validation
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