The ambiguity of data science team roles and the need for a data science workforce framework

Jeffrey S. Saltz, Nancy W. Grady

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

This paper first reviews the benefits of well-defined roles and then discusses the current lack of standardized roles within the data science community, perhaps due to the newness of the field. Specifically, the paper reports on five case studies exploring five different attempts to define a standard set of roles. These case studies explore the usage of roles from an industry perspective as well as from national standard big data committee efforts. The paper then leverages the results of these case studies to explore the use of data science roles within online job postings. While some roles appeared frequently, such as data scientist and data engineer, no role was consistently used across all five case studies. Hence, the paper concludes by noting the need to create a data science workforce framework that could be used by students, employers, and academic institutions. This framework would enable organizations to staff their data science teams more accurately with the desired skillsets.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
EditorsJian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2355-2361
Number of pages7
ISBN (Electronic)9781538627143
DOIs
StatePublished - Jul 1 2017
Event5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States
Duration: Dec 11 2017Dec 14 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume2018-January

Other

Other5th IEEE International Conference on Big Data, Big Data 2017
CountryUnited States
CityBoston
Period12/11/1712/14/17

Keywords

  • big data
  • data science
  • data science roles
  • project management

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Optimization

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  • Cite this

    Saltz, J. S., & Grady, N. W. (2017). The ambiguity of data science team roles and the need for a data science workforce framework. In J-Y. Nie, Z. Obradovic, T. Suzumura, R. Ghosh, R. Nambiar, C. Wang, H. Zang, R. Baeza-Yates, R. Baeza-Yates, X. Hu, J. Kepner, A. Cuzzocrea, J. Tang, & M. Toyoda (Eds.), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017 (pp. 2355-2361). (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2017.8258190