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

Jeffrey S. Saltz; Nancy W. Grady

doi:10.1109/BigData.2017.8258190

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

Jeffrey S. Saltz, Nancy W. Grady

School of Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Editors	Jian-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
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2355-2361
Number of pages	7
ISBN (Electronic)	9781538627143
DOIs	https://doi.org/10.1109/BigData.2017.8258190
State	Published - Jul 1 2017
Event	5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States Duration: Dec 11 2017 → Dec 14 2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume	2018-January

Other

Other	5th IEEE International Conference on Big Data, Big Data 2017
Country	United States
City	Boston
Period	12/11/17 → 12/14/17

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

Access to Document

10.1109/BigData.2017.8258190

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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

The ambiguity of data science team roles and the need for a data science workforce framework. / Saltz, Jeffrey S.; Grady, Nancy W.

Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. ed. / Jian-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. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2355-2361 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Saltz, JS & Grady, NW 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. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 2355-2361, 5th IEEE International Conference on Big Data, Big Data 2017, Boston, United States, 12/11/17. https://doi.org/10.1109/BigData.2017.8258190

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

Saltz, Jeffrey S. ; Grady, Nancy W. / The ambiguity of data science team roles and the need for a data science workforce framework. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. editor / Jian-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. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2355-2361 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017).

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