Demystifying Job Roles in Data Science: A Text Mining Approach

  • Date: 15.10.2021
  • The continuing proliferation of data science these days is causing organizations to reassess their workforce demands. Simultaneously, it is unclear what types of job roles, knowledge, skills, and abilities make up this field and how they differ. This ambiguity is generating a misleading myth around the data scientist’s role. Against this background, this project attempts to provide clarity about the heterogeneous nature of job roles required in the field of data science by processing 25,104 job advertisements published at the online job platforms Indeed, Monster, and Glassdoor. We propose a text mining approach combining topic modeling, clustering, and expert assessment. Therefore, we identify and characterize six job roles in data science that are in a request by organizations, described by topics classified in three major knowledge domains. An understanding of job roles in data science can help organizations in acquiring and cultivating job roles to leverage data science effectively.

    Methodological Approach

     

    Publications

     

    • Demystifying Job Roles in Data Science: A Text Mining Approach Michalczyk, Sven; Nadj, Mario; Mädche, Alexander; Gröger, Christoph; ECIS 2021 Proceedings - European Conference on Information Systems. Human Values Crisis in a Digitizing World, Paper Number: 1622, Association for Information Systems (AIS)