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.