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Unveiling Data Science Team Roles and Competencies: A Literature-Based Analysis
Christian Haertel, Maike Holtkemper, Daniel Staegemann, Christian Beecks, Klaus Turowski
With record amounts of data being generated each year, Data Science (DS) aims to extract valuable knowledge from this resource and, thus, has gained notable interest from organizations. However, the envisioned improvements in performance can only be realized upon successful project completion. The literature considers the project team and the appropriate competencies as essential factors for DS project success. However, the definition of roles is lacking in DS process models, and existing competency frameworks predominantly focus on the Data Scientist as an omnipotent actor. Hence, in this paper, an integrative perspective is pursued through a systematic literature review, aiming to identify common DS team roles and competencies. Based on these findings, five DS role categories are derived and mapped with the associated competencies. Therefore, this work contributes to facilitating DS team composition.
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