Senior Data Scientist

• Design and implement signal processing pipelines to analyse non-invasive physiological data
• Develop algorithms and models to extract clinically relevant cardiorespiratory and haemodynamic metrics
• Analyse complex time-series data from wearable sensors, including noisy real-world signals
• Support experimental design and analyse data from internal testing and controlled clinical studies
• Collaborate with engineering, data science, and clinical teams to integrate algorithms into products

• Strong experience in signal processing and analysis of time-series or physiological data
• Experience developing algorithms or models using MATLAB, Python, or similar high-level tools
• Understanding of techniques such as filtering, noise reduction, and feature extraction
• Experience working with non-invasive physiological signals (e.g. ECG, PPG, respiratory data)
• Ability to design experiments and work with real-world and clinical datasets

Nice to have

• Experience working with wearable sensors or digital health technologies
• Exposure to machine learning techniques applied to signal or physiological data
• Understanding of cardiorespiratory physiology or haemodynamics
• Experience translating algorithms into production or embedded environments
• Familiarity with C/C++ or similar for deployment

If you're a Data Scientist with strong signal processing experience and an interest in applying your work to real-world physiological challenges, we'd love to hear from you.

Cure Talent are delighted to be partnered with an emerging wearable medical technology company at a defining stage of its growth. Developing next-generation physiological monitoring solutions, this organisation is advancing its data science and sensing capabilities to deliver medical-grade insights beyond the hospital environment.