Public Expectations of Professional Expertise: Skills and Knowledge in Data Science, Law, and Other Occupations

• In Event: 413 - Section on Organizations, Occupations and Work Refereed Roundtable Session. Table 01. Culture and Organizations
  In Refereed Roundtable 100min: Table 17. Occupations and Professions

Abstract

This article studies the emerging group of data science experts in comparison to law and other familiar cases, with respect to the public salience of their arcane knowledge. It formally analyzes structures of expert skills on the basis of a large corpus of textual job descriptions (>50k) in order to consider the role of abstract knowledge, relative to informal, organizational and institutional processes, as source of public recognition. Data scientists are seen to have combined expertise form distinct specializations. They resemble the canonical legal profession in encountering expectations that require them to transpose knowledge from one context to another. Unlike occupations focused on singular industries, data science skills apply across organizational forms. Three contributions follow. First, this study provides the first systematic account of the data science profession and finds a distinct substantive foundation. Second, it develops a strategy to empirically analyze abstract knowledge, the basis of professional work. This strategy reveals formalisms connecting specializations as a source of public recognition. Third, the article reconciles a longstanding divide in the literature and considers a new direction in expert groups that arise with the shift from bureaucratic and scientific problems toward technological problems.

Author

• Philipp Soeren Brandt, University of Mannheim