The hybrid work of public sector data scientists

Abstract

Abstract As algorithms play an increasingly important role in public organizations, we see a rise in the number of public sector data scientists. Even though the relevance and risks of algorithms in the public sector are broadly discussed, our current academic knowledge of public sector data scientists and their work is limited. To develop an understanding of their work practices, data scientists have been studied in two Dutch government organizations. In a core period of 5 months per organization, I conducted in-depth qualitative research into the work of the data scientists, their role in the organization, and their relationship with other actors at two regulatory agencies in the Netherlands. The analysis shows that data scientists integrate Silicon Valley and engineering, domain, as well as political–administrative logics in their work practices. Thus, the work of the data scientists is hybrid. However, even though the organizational contexts are very similar, hybrid work takes very different forms both across organizations and over time. This dynamic hybridity is linked to different algorithmization processes and outcomes in the two organizations. The results suggest that hybridity in public sector data scientists’ work should be adapted to organizational and technological aspects of transformation processes and aspired outcomes.