Employability skills: Profiling data scientists in the digital labour market

Francesco Smaldone, Adelaide Ippolito, Jelena Lagger, Marco Pellicano

Research output: Contribution to journalArticlepeer-review

38 Citations (SciVal)

Abstract

In the current scenario, data scientists are expected to make sense of vast stores of big data, which are becoming increasingly complex and heterogeneous in nature. In the context of today's rapid technological development and its application in a growing array of fields, this role is evolving simultaneously. The present study provides an insight into the current expectations of employers seeking to hire individuals with this job title. It is argued that gaining a better understanding of data scientists’ employability criteria and the evolution of this professional role is crucial. The focus is placed on the desired prerequisites articulated through job advertisements, thus deriving relevant means for furthering theory and practice. It was achieved by harvesting relevant data from job advertisements published on US employment websites, which currently attract the US market's highest recruitment traffic. The key contribution of this study is to have identified means of systematically mapping skills, experience, and qualifications sought by employers for their data scientists, thus providing a data-driven pathway for employability and avoiding skills gaps and mismatches in a profession that is pivotal in the Industry 4.0.
Original languageEnglish
Pages (from-to)671-684
Number of pages14
JournalEuropean Management Journal
Volume40
Issue number5
Early online date21 Jun 2022
DOIs
Publication statusPublished - 1 Oct 2022

Keywords

  • Data scientist
  • Employability
  • Labour market
  • Skills
  • Text mining
  • Topic modelling

Fingerprint

Dive into the research topics of 'Employability skills: Profiling data scientists in the digital labour market'. Together they form a unique fingerprint.

Cite this