Data Scientist (Series C Silicon Valley Startup, 70mil funding)
They are looking for a passionate Data Scientist to develop impactful healthcare solutions using wearable data. This high-impact role provides an opportunity to shape the future of digital health and bring clinically validated, regulatory-ready Machine Learning solutions to market.
What you'll do:
As a Data Scientist, you will play a key role in building real-time, FDA-compliant algorithms that analyse continuous physiological signals from wearables. Your work will involve designing machine learning models for real-time analysis of wearable biosignal data such as ECG, PPG, accelerometer.You will also be responsible for developing algorithms that meet clinical-grade performance standards for use in regulated environments. Collaborating with various teams will be a significant part of your role to ensure solutions align with FDA, SaMD, and GMLP requirements.
- Design and implement machine learning models for real-time analysis of wearable biosignal data.
- Develop algorithms that meet clinical-grade performance standards for use in regulated environments.
- Preprocess and manage large-scale, continuous time-series datasets from wearable sensors.
- Collaborate with clinical, product, and regulatory teams to ensure solutions align with FDA, SaMD, and GMLP requirements.
- Optimize algorithms for deployment on resource-constrained devices.
- Run thorough validation experiments including performance metrics like sensitivity, specificity, ROC-AUC, and precision-recall.
- Contribute to technical documentation and regulatory submissions for medical-grade software.
What you bring:
The ideal candidate for this Data Scientist role will have an MS or PhD in Machine Learning, Biomedical Engineering, Computer Science or a related field. You should have 3–5+ years of experience applying machine learning to time-series or physiological data.A strong foundation in signal processing and time-series modelling is essential. Proficiency in Python and ML frameworks such as PyTorch or TensorFlow is required. Familiarity with FDA regulatory pathways for medical software is crucial.
- MS or PhD in Machine Learning, Biomedical Engineering, Computer Science, or a related field.
- 3–5+ years of experience applying machine learning to time-series or physiological data.
- Strong foundation in signal processing and time-series modelling.
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
- Familiarity with FDA regulatory pathways for medical software.
- Experience with MLOps practices and model versioning in compliant environments.
Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates