At a Glance
- Tasks: Design algorithms for wearable tech that monitors health in real-time.
- Company: Join a cutting-edge wearable medical technology company at a pivotal growth stage.
- Benefits: Competitive salary, flexible working, and opportunities for professional development.
- Other info: Collaborative environment with strong career growth potential.
- Why this job: Make a real impact on healthcare by developing innovative monitoring solutions.
- Qualifications: Experience in signal processing and analysis of physiological data is essential.
The predicted salary is between 50000 - 70000 £ 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 designed to deliver medical-grade insights beyond the hospital environment, the business is advancing its sensing and data science capabilities to enable continuous monitoring of key physiological parameters across a range of care settings.
We have an opportunity for an Algorithm Engineer to join the Data Science team and support the development of algorithms and modelling techniques used to interpret complex physiological signals collected from non-invasive wearable sensors. As the Algorithm Engineer, you will design signal processing pipelines and analytical models capable of extracting clinically meaningful cardiorespiratory and haemodynamic metrics from real-world sensor data. The work sits at the intersection of signal processing, physiological modelling and applied data science, translating advanced sensing technologies into reliable clinical insights.
This is a hands-on position working closely with data science, engineering and clinical teams to develop and refine algorithms that underpin the organisation’s wearable monitoring technology. The role will also contribute to experimental design and the analysis of datasets generated through internal testing and controlled clinical studies.
To be successful as the new Algorithm Engineer, you will bring strong experience in signal processing and analysis of physiological or time-series data. You will be comfortable developing algorithms or modelling techniques used to interpret complex biosignals and capable of translating theoretical approaches into practical implementations that support product development.
Key Responsibilities- Design and implement signal processing pipelines to analyse non-invasive physiological signals collected from wearable sensors.
- Develop algorithms and modelling techniques to extract clinically meaningful metrics related to cardiorespiratory and haemodynamic function.
- Analyse complex physiological time-series data including signals such as ECG, PPG and other non-invasive biosignals.
- Support the design of experiments and analyse data generated through internal testing and controlled clinical studies.
- Work closely with Data Science and Engineering teams to integrate algorithms into software systems and product architectures.
- Collaborate with clinical and product teams to ensure algorithms are aligned with physiological understanding and clinical requirements.
- Demonstrated experience in signal processing and analysis of physiological or time-series data.
- Strong understanding of signal processing techniques including filtering, noise reduction and feature extraction.
- Experience developing algorithms or modelling techniques used to interpret physiological signals.
- Experience working with non-invasive physiological signals, particularly cardiorespiratory or haemodynamic signals.
- Programming experience using environments commonly used for signal processing and modelling such as MATLAB, Python or similar high-level languages.
- Experience designing experiments and analysing data generated through controlled studies or experimental testing.
- Bachelor’s degree in Electrical Engineering, Biomedical Engineering, Computer Science, Physics, Applied Mathematics or a related quantitative discipline is required.
- A Master’s or PhD in a relevant field would be advantageous.
This is a high-impact opportunity within a growing wearable MedTech business where signal processing and physiological modelling are central to the development of next-generation monitoring technologies. It will suit an engineer or scientist who enjoys solving complex signal challenges and contributing directly to the translation of innovative sensing technologies into clinically meaningful insights.
Algorithm Engineer employer: Cure Talent
Join a pioneering wearable medical technology company that is at the forefront of innovation in physiological monitoring solutions. As an Algorithm Engineer, you will thrive in a collaborative work culture that values creativity and scientific inquiry, with ample opportunities for professional growth and development. Located in a dynamic environment, this role offers the chance to make a significant impact on healthcare by translating advanced sensing technologies into reliable clinical insights.
StudySmarter Expert Advice🤫
We think this is how you could land Algorithm Engineer
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cure Talent.
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We think you need these skills to ace Algorithm Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cure Talent, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cure Talent. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cure Talent
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cure Talent!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
