Biomedical data scientists across the UK cannot easily move between universities, hospitals, and companies because there is no shared language to describe what they do. This matters because data science expertise is in extremely high demand, yet the field lacks a common framework for roles, skills, and career pathways. Without this, organisations struggle to build effective data science teams, and talented people get stuck in one sector. The project will map the entire UK biomedical data science ecosystem—identifying skills gaps, clarifying job functions, and documenting how collaborative team science works in practice. If successful, the work will create a standard vocabulary for data science roles and competencies. This would let researchers move more freely between academia, the NHS, and industry, increasing the overall workforce and making research more efficient. It would also make career paths transparent, helping a wider range of people enter and progress in the field. The Alan Turing Institute and EMBL-EBI are leading the effort, drawing on their existing networks to ensure the framework works across different organisations.
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Data and data science are transforming the world and data science expertise is in extremely high demand. Particularly within biomedical research, there is an urgent need for a shared framework of data functions, to enable skills mobility and recognition across different contexts (MRC strategic review 2022). This project will enable organisations to incorporate data science skills into their teams and work culture by establishing a greater understanding of the common language needed to describe skills and careers in biomedical data science. We will enable cross-domain working so that collaborative team science approaches lead the future of biomedical research. Our proposal to advance biomedical data science careers will focus on three key objectives: To evaluate skills gaps and identify priority areas for developing knowledge, skills and behaviours across the biomedical data science ecosystem. 2. To better understand roles, career pathways and team science approaches within the biomedical data science community and how these can improve access, resourcing and career offers. 3. To evaluate and recommend innovative approaches and ways of working that will drive forward capacity building and improve quality and standards in biomedical data science. We will conduct an extensive landscape mapping exercise to evaluate the biomedical data science ecosystem in terms of competencies, skills, career pathways and team science approaches. This will constitute a comprehensive basis to improve the development of biomedical data science skills and career offers and, ultimately, support innovation to improve capacity, quality and standards in biomedical data science. The Alan Turing Institute and EMBL's European Bioinformatics Institute (EMBL-EBI) are world leaders in biomedical data science with proven track records of innovative and impactful collaborative team science, and we will leverage existing cross-sector networks and interest groups to provide a wide range of partners to inform this work. The outcomes of this work have the potential to directly affect how biomedical data science is conducted as well as improve the research culture and career opportunities for biomedical data science across the UK. This improvement will positively impact sector porosity, supporting greater mobility between organisations in different sectors, increasing the overall workforce, and leading to greater efficiency in research. In addition, our approach will embed and champion equity, diversity and inclusion (EDI) by ensuring we conduct the project in a manner that enables diverse and inclusive input from the biomedical data science community and beyond. This will lead to more impactful outputs that will provide transparency of roles, career paths and ways of working, which will allow for democratisation of knowledge in terms of careers in biomedical data science and will create opportunities for a greater variety of people, skills and roles in teams leading to truly diverse teams.
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