Clinical Data Scientist

About the role

As a Clinical Data Scientist, you will work at the intersection of physiological sensing, clinical science, and data analysis, transforming multimodal wearable signals into scientifically rigorous, research- and regulator-ready datasets. You will work closely with clinicians, physiological scientists, researchers, and ML teams to understand what the signals represent, establish their quality and validity, and extract robust evidence across clinical studies.

What you’ll do

• Design and implement analysis pipelines for multimodal physiological data, including PPG, cardiovascular acoustics, IMU, and temperature.
• Clean, synchronise, characterise, and validate real-world physiological datasets affected by motion, context, missingness, and sensor variability.
• Develop methods for signal-quality assessment, physiological feature extraction, annotation, and dataset quality control.
• Analyse relationships between wearable signals, clinical reference measurements, interventions, and physiological state.
• Support clinical study design, experimental protocols, and data-collection strategies to ensure scientifically meaningful datasets.
• Work with ML scientists to define analysis-ready datasets, labels, endpoints, and validation strategies.
• Develop reproducible workflows for dataset versioning, provenance, statistical analysis, and scientific reporting.
• Ensure clinical data meet appropriate governance, privacy, traceability, and regulatory requirements.

What we expect

• Strong experience in physiological/biomedical time-series analysis, signal processing, or clinical data science.
• Proficiency in Python and scientific/data-analysis frameworks.
• Experience working with clinical, biomedical, wearable, or biosignal datasets.
• Good understanding of experimental design, statistics, signal quality, variability, bias, and reproducibility in health research.
• Ability to reason critically about noisy physiological data — not simply process it.
• Ability to collaborate closely with clinical scientists, ML researchers, and engineers.

‍

Why OmniBuds

You’ll help build the clinical evidence foundation for a new class of ear-based cardiovascular biomarkers—shaping how wearable health data is trusted, interpreted, and deployed at scale.