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

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
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article

Policy briefing - Diversifying Professional Roles in Data Science

1 citations
Zenodo (CERN European Organization for Nuclear Research)
Interdisciplinary Research and Collaboration
4.17
article

Policy briefing - Diversifying Professional Roles in Data Science

article en
1 citations

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
The Alan Turing Institute (GB), OLS
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Interdisciplinary Research and Collaboration
4.17
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Policy briefing - Diversifying Professional Roles in Data Science · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS