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Hiring, Managing, and Retaining Data Scientists and Research Software Engineers in Academia: A Career Guidebook from ADSA and the US-RSE

Authors: Van Tuyl, Steve (Ed.);

Hiring, Managing, and Retaining Data Scientists and Research Software Engineers in Academia: A Career Guidebook from ADSA and the US-RSE

Abstract

The importance of data, software, and computation has been recognized in academia and is reflected in the recent rise of job opportunities for data scientists and research software engineers. Big data, for example, created a wave of novel job descriptions before the term Data Scientist (DS) was widely used. Even though software has become a major driver for research (Nangia and Katz, 2017), Research Software Engineer (RSE) as a formal role has lagged behind in terms of job openings, recognition, and prominence within the community. The value of DS/RSE roles is not widely recognized in the academic community yet, and research data, software, and workflows are, in many domains, still regarded as by-products of research. Data Scientists and Research Software Engineers (DS/RSEs) face similar challenges when it comes to careers paths in academia - both are non-traditional academic professions with few incentives and a lack of clear career trajectories. This guidebook presents the challenges and suggestions for solutions to improve the situation and to reach a wide community of stakeholders needed to advance career paths for DS/RSEs.

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Keywords

data science, career guidebook, research software engineering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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