Biomedical Data Science and Careers Leadership Group

There is a growing need for highly skilled biomedical data scientists in academia and industry to tackle important societal challenges. Whilst there are a multitude of early career training opportunities in data science, there remain barriers to progression into leadership roles which make careers in the area less attractive and less accessible. In academia, one of the key challenges for data scientists is that they often take supporting roles in developing and implementing methodology alongside a wide range of academics in different scientific and clinical fields. Current academic promotion pathways focus on an individual's contribution as a leader on research papers and grant applications, and place value on a clear academic vision and direction. Such benchmarks create a challenge for those in supporting roles and recognition of the valued contribution made by skilled biomedical data scientists to research is often limited. Beyond academia, data scientists are a key workforce in industry and the public sector, including the NHS. In these sectors, with the strong recent influence of AI methodology, these new careers are much more varied and less well understood. As a result of this, interactions, knowledge exchange and career permeability between academic and other sectors are presently limited. Equally, there remains a need to increase the level of commercial exploitation of academic research in biomedical data science and to increase entrepreneurship among biomedical data scientists at all career stages. This project aims to address the issues above through several related objectives. It will map career pathways and barriers to progression in academia and make recommendations to address the issues raised. Career pathways in partner organisations in other sectors will also be researched, and results will be collated into career advice materials for data scientists, and for use with students and early career researchers in academia. Results from these investigations will be used to inform a new mentorship programme for biomedical data scientists at relevant career stages. Alongside this, the project will implement initiatives to encourage research and career interactions and exchanges between academic and other sectors. Finally, steps to increase entrepreneurship in the biomedical data science workforce will be taken, increasing awareness and providing effective training, and increasing the level of commercialization of academic research. Academic partners on the project are the Universities of Leeds, Sheffield, York, Teesside and Newcastle. Their active involvement will ensure that best practice in academic and data science careers is identified, and that any recommendations from the project are broadly applicable. The project will also have partners from industry and other sectors. At the time of writing this summary, a broad range of industrial and public sector organizations have been contacted to request involvement. Several have already become formal partners: these include small and large companies, for example Pinpoint Data Science, AstraZeneca and GlaxoSmithKline, the NHS (West Yorkshire Integrated Care Board) and a trade body (the Association of British Health Tech Industries). The project will improve biomedical data science careers in all sectors, attracting talented individuals to this area and helping to retain valuable individuals in the workforce. Data science is increasingly involved in almost all biomedical research projects in academia, industry and other sectors, and ultimately this project will benefit the UK by significantly increasing the quality of this research.