Policy briefing - Diversifying Professional Roles in Data Science
The interdisciplinary nature of the data science workforce extends beyond the traditional notion of a "data scientist." A successful data science team requires a wide range of technical expertise, domain knowledge and leadership capabilities. To strengthen such a team-based approach, this note recommends that institutions, funders and policymakers invest in developing and professionalising diverse roles, fostering a resilient data science ecosystem for the future. By recognising the diverse specialist roles that collaborate within interdisciplinary teams, organisations can leverage deep expertise across multiple skill sets, enhancing responsible decision-making and fostering innovation at all levels. Ultimately, this note seeks 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. This work was funded through The Alan Turing Institute's Skills Policy Awards 2023-24, which is supported by the Ecosystem Leadership Award under the EPSRC Grant EP/X03870X/1 and The Alan Turing Institute.
Institutions
- The Alan Turing Institute (GB)
- OLS
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-03
- DOI
- https://doi.org/10.5281/zenodo.14946850
- Citations
- 1
- Primary Topic
- Interdisciplinary Research and Collaboration
- Type
- article
- Field-Weighted Citation Impact
- 4.17