comind - Principal Data Scientist

• Act as the technical authority for the end-to-end signal processing and inference chain for CoMind’s technologies: from raw optical data through to clinical measurements • Set the methodological direction for estimation, signal extraction and ML modelling across the team: which approaches suit which problems, how they are evaluated, and what evidence is required before a method is trusted. • Own signal processing and analysis programmes from research through to validated, production-quality implementations with Software Engineering. • Derive achievable performance bounds from instrument and noise models, and use them to drive algorithm selection, requirement setting and design trade-offs • Own how the team handles uncertainty and calibration — inference methods appropriate to small clinical cohorts, per-patient estimation with quantified uncertainty, and calibration strategies that make measurements comparable across devices, sessions and patients. • Set the standard for how the data science function works: reproducibility, analysis and code review, experiment design, dataset governance and ground-truth definitions • Act as the primary technical reviewer and expert resource across the research organisation, reviewing technical reports, analysis plans and evaluation methodology, and holding the bar for methodological rigour and scientific integrity. • Identify and introduce new, best-practice methods from estimation, inference and measurement science in adjacent fields. • Act as a mentor to members of the Data Science teams and across the wider business • Contribute to CoMind's IP and publication strategy, authoring and reviewing technical papers, patent applications and regulatory documents. • AI is fundamental to our culture. It's not just a tool, but a core part of how we work, collaborate, and innovate. We expect all team members to embrace AI in their daily work and continuously find new ways to use it effectively.