How Engineers Perform Data Science Work: Designing Hybrid Roles

Amelie L. Schmid () and Manuel Wiesche ()
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Amelie L. Schmid: TU Dortmund University
Manuel Wiesche: TU Dortmund University

A chapter in Solutions and Technologies for Responsible Digitalization, 2025, pp 183-199 from Springer

Abstract: Abstract As of today, organizations are still struggling to derive consistent value from data science projects. The basic relevance of domain knowledge for data science work can be considered as common sense. Engineers, in particular, offer a unique view of emerging data science work based on their critical role within traditional industries. As a constraint, current studies on data science work consider domain experts as rather passive, and engineering-related studies are rare. To further explore these challenges, the present study analyses the data science work of 30 engineers at an international automotive supplier. By investigating three cases, the evolvement of hybrid data science work can be derived, by combining two perspectives: engineering and data science. Thus, engineers actively incorporate the data science perspective, particularly when development activities involve minimal participation of data scientists. This contribution significantly enhances existing knowledge by demonstrating how engineers embrace the data scientists’ perspective and perform hybrid data work.

Keywords: Data science work; Data scientists; Engineers; Hybrid practice; Transformation of work (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-80122-8_12

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