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- Tasks: Develop algorithms to analyse physiological data from wearable sensors and create impactful medical insights.
- Company: Join an innovative wearable medical tech company at a pivotal growth stage.
- Benefits: Competitive salary, flexible working options, and opportunities for professional development.
- Other info: Collaborative environment with a focus on cutting-edge technology and career advancement.
- Why this job: Make a real difference in healthcare by translating complex data into meaningful insights.
- Qualifications: Strong background in signal processing and experience with MATLAB or Python.
The predicted salary is between 60000 - 80000 £ per year.
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.
We have an opportunity for a Senior Data Scientist (Signal Processing) to join the team and play a key role in developing algorithms and modelling techniques used to interpret complex physiological data from non-invasive wearable sensors. This is a hands-on, technically focused role working at the intersection of signal processing, machine learning, and physiology, translating real-world sensor data into clinically meaningful insights.
Key responsibilities
- 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
Experience and skills required
- 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.
Senior Data Scientist (Signal Processing) employer: Cure Talent
Contact Detail:
Cure Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Signal Processing)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to signal processing and physiological data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with algorithms and time-series data, and don’t forget to highlight any hands-on projects you've worked on.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals like you. Make sure to tailor your application to highlight your relevant experience in signal processing and wearable technologies.
We think you need these skills to ace Senior Data Scientist (Signal Processing)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in signal processing and time-series analysis. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or technologies you've worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about wearable medical technology and how your background makes you a perfect fit for our team. Let us know what excites you about the role!
Showcase Your Technical Skills: Since this role is hands-on, make sure to mention your proficiency in MATLAB, Python, or any other relevant tools. If you've developed algorithms or models before, share those experiences with us – we love seeing practical applications of your skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company and culture!
How to prepare for a job interview at Cure Talent
✨Know Your Signal Processing Inside Out
Make sure you brush up on your signal processing knowledge. Be ready to discuss techniques like filtering, noise reduction, and feature extraction in detail. Prepare examples of how you've applied these methods in past projects, especially with physiological data.
✨Showcase Your Coding Skills
Since the role requires experience with MATLAB, Python, or similar tools, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice writing clean, efficient code that relates to algorithm development or data analysis.
✨Understand the Clinical Context
Familiarise yourself with the clinical applications of your work. Be ready to explain how your algorithms can translate complex physiological data into meaningful insights. Showing an understanding of cardiorespiratory physiology or haemodynamics will definitely set you apart.
✨Prepare for Collaboration Questions
This role involves working closely with engineering, data science, and clinical teams. Think of examples where you've successfully collaborated across disciplines. Highlight your communication skills and how you’ve integrated feedback from different teams into your projects.