Professionalising Data Stewards and all the 'others'

This presentation was given on 18th September 2025 at the CaSDaR launch event in Birmingham, UK. CaSDaR website - https://casdar.ac.uk/ Abstract: The interdisciplinary nature of the data science workforce extends beyond the traditional notion of a "data scientist" and we should therefore recognise and strive to professionalise all the ‘other’ roles that are part of the data science workforce. A successful data science team requires a wide range of technical expertise, domain knowledge and leadership capabilities. To strengthen such a team-based approach, we (myself and Malvika Sharan) recommend that institutions, funders and policymakers invest in developing and professionalising a more diverse set of roles, including digital research technical professional roles, such as data stewards, therefore fostering a resilient data science ecosystem for the future. To move towards professionalising these diverse roles there is a need to create a better understanding of them through qualitative research – investigation of what roles exists, documenting competencies and surfacing knowledge of approaches to integrating specialist roles into data science teams. I will highlight work we have done in this area, including The Turing Way project - Professionalising traditional and infrastructure research roles in data science, in which we documented the different roles and competencies that make up data science teams at Turing and my current project, Advancing Biomedical Data Science Careers, which seeks to understand the current landscape of skills, roles and team approaches in this area. By recognising and professionalising these diverse specialist roles and how they collaborate within interdisciplinary teams, organisations can leverage deep expertise across multiple skill sets, enhancing responsible decision-making and fostering innovation at all levels. Ultimately, we seek to shift the perception of data science professionals from the conventional view of individual data scientists to a competency-based model of specialist roles within a team, each essential to the success of data science initiatives. See policy briefing note here: https://doi.org/10.5281/zenodo.14946850