Data Scientist - Experimentation

At CoMind, we are developing a non-invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting-edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world.

The Role:

As a Data Scientist at CoMind, you will join a multidisciplinary team working at the intersection of neurophysiology, optics, machine learning, and signal processing. Your focus will be on analysing multidimensional time-series datasets collected by our next-generation neural sensor in both clinical trial and in-house experimental settings.

You will play a key role in interpreting physiological and optical signals to derive actionable insights that inform product development and clinical decision-making. You will also work closely with the Translational Optics team on designing and running in-vivo data acquisition experiments.

Please note that this role requires 4 days per week in the office.

Responsibilities:

• Conduct exploratory data analysis on complex time-series datasets generated from clinical trials, internal studies, and external research databases.

• Develop, prototype, and apply signal processing and machine learning models to interpret physiological signals such as cerebral blood flow, cerebral autoregulation

• Assist in the laboratory with in-vivo testing and implementation of new neuromonitoring systems and methods

• Design and validate algorithms for denoising, signal demixing, classification, and interpretation of neuromonitoring data.

• Collaborate with domain experts to translate clinical and physiological requirements into robust data analysis workflows.

• Write high-quality, well-tested Python code that meets industry standards for medical-grade software and supports FDA regulatory pathways.

• Produce clear and insightful white papers, documentation, and visualisations for both technical and non-technical stakeholders.

• Participate in internal research planning by gathering requirements, scoping work items, and contributing to roadmap discussions.

Skills & Experience:

• Strong background in physiological signal analysis, ideally with experience in neurophysiology, cerebral hemodynamics, or related areas

• Proficient in applying statistical modelling and machine learning techniques (e.g., time-series modelling, feature extraction, classification) to biological/medical datasets

• >2 years of experience in a research or applied data science role, ideally involving cross-disciplinary collaboration with clinical or experimental teams

• Fluent in Python and familiar with industry-standard tools for version control, data engineering, and reproducible research workflows

• Comfortable working in a fast-paced, research-driven environment with a strong sense of ownership and a willingness to learn and experiment

• Excellent written and verbal communication skills for conveying complex results clearly to technical and non-technical stakeholders.

Nice to have:

• Experience undertaking laboratory testing and development of physiological measurement systems, including device application, data acquisition and analysis

• Hands-on experience with in-vivo physiological signal acquisition using experimental technologies

Benefits:

• Company equity plan

• Company pension scheme

• Private medical, dental and vision insurance

• Group life insurance

• Comprehensive mental health support and resources

• Unlimited holiday allowance (+ bank holidays)

• Weekly lunches

• Breakfast and snacks provided.