Data Scientists’ Identity Work: Omnivorous Symbolic Boundaries in Skills Acquisition

Abstract

Drawing on theories from the sociology of work and the sociology of culture, this article argues that members of nascent technical occupations construct their professional identity and claim status through an omnivorous approach to skills acquisition. Based on a discursive analysis of 56 semi-structured in-depth interviews with data scientists, data science professors and managers in Israel, it was found that data scientists mobilise the following five resources to construct their identity: (1) ability to bridge the gap between scientist’s and engineer’s identities; (2) multiplicity of theories; (3) intensive self-learning; (4) bridging technical and social skills; and (5) acquiring domain knowledge easily. These resources diverge from former generalist-specialist identity tensions described in the literature as they attribute a higher status to the generalist-omnivore and a lower one to the specialist-snob.

Future of Professional Work: Evidence from Legal Jobs in Britain and the United States

“…When one profession is emergent, observable jurisdictional settlements are more akin to temporary staging posts in a long trajectory to establish legitimacy (Baba, Sasaki and Vaara 2021). Nevertheless, our evidence is consistent with interpreting jurisdictional settlements between distant professions as a move towards connective professionalism that hinges on relational agency (Avnoon 2021;Edwards 2011;Noordegraaf 2020). We respond to Noordegraaf 's call for more detailed empirical work on connective professionalism (Noordegraaf and Brock 2021).…”

“…The practical application of data science knowledge requires a bundle of skills that involve writing code using a variety of programming languages. The social status of the coding elite (Burrell and Fourcade 2021) is said to be underpinned by data scientists' omnivorous approach to skill acquisition and domain expertise (Avnoon 2021). Brandt provides ample evidence from his fieldwork that "data nerds" never initiate jurisdictional conflicts due to the emergent nature of data science as a profession.…”

Contextualizing Ai Ethics in Time and Space

“…Finally, we show that while data science is a nascent profession, these three moral logics in fact stem from the techno-libertarian culture of its parent-professionengineering (Avnoon 2021), and that they accordingly prevent the institutionalization of a wider, agreed-upon moral regime. While our findings echo other recent studies on tech ethics in other parts of the world (Metcalf, Moss, & boyd 2019;Orr & Davis 2020;Ribak 2019), suggesting this might be a global techno-professional moral regime, our findings can also be explained through their particular national context -namely, the Israeli one.…”

Datenwissenschaften und Gesellschaft

“…Data Scientists werden in vielen der zitierten Studien als multidisziplinär orientierte Praktiker*innen imaginiert, die als sogenannte »data unicorns« (Hermida & Young 2017) über eine ganze Reihe verschiedener Kompetenzen verfügen sollen. In einer kultursoziologischen Perspektive werden Data Scientists sodann als ›Allesfres-ser‹ (omnivores) bezeichnet, die ihre professionelle Identität durch einen generalistischen, inklusiven Zugang zum Kompetenzerwerb konstruieren und aufrechterhalten würden (Avnoon 2021). Die grundlegende Distinktion gegenüber anderen Berufsgruppen erfolge gerade nicht durch Spezialisierung, sondern durch eine generalistische Haltung, die Expertise für unterschiedlichste Gegenstände beansprucht (ebd.…”