Hiring, Managing, and Retaining Data Scientists and Research Software Engineers in Academia: A Career Guidebook from ADSA and US-RSE
Contributors
Editor:
Project members:
- Beck, David1
- Cosden, Ian2
- Joyce, Blake3
- Liu, Jing4
- Maimone, Christina5
- McHenry, Kenton6
- Parker, Micaela7
- Agate, Nicky8
- Alonzi, Peter9
- Burgess, Arlyn9
- Cleveland, Sean10
- Culich, Aaron11
- Daniels, Mike12
- Davis, Alex13
- Davis, Sarah14
- Gesing, Sandra15
- Greer, Launa16
- Holdgraf, Chris17
- Katz, Daniel S.6
- Levy, Rachel18
- Markelz, R.J. Cody11
- Merchant, Nirav19
- Michael, Scott20
- Mills, Bill21
- Oliver, Tiffany22
- Orso, Alessandro23
- Pomann, Gina-Maria24
- Rasool, Rahim16
- Ratamero, Erick25
- Riemer, Kristina19
- Spreadbury, Trevor16
- Stone, Sarah1
- Sweeney, Jess16
- Tomko, Karen26
- Tomlinson, William J.27
- Uminsky, David16
- Vareth, Maryam28
- Vásquez, Váleri N.11
- Vu, Elizabeth29
- Wilson, Bruce E.30
- Young, Jeffrey23
- 1. University of Washington
- 2. Princeton University
- 3. University of Alabama at Birmingham
- 4. University of Michigan
- 5. Northwestern University
- 6. University of Illinois Urbana Champaign
- 7. Academic Data Science Alliance
- 8. Carnegie Mellon University
- 9. University of Virginia
- 10. University of Hawaii System
- 11. University of California, Berkeley
- 12. Ronin Institute, National Center for Atmospheric Research
- 13. The Ohio State University
- 14. Renaissance Computing Institute, University of North Carolina, Chapel Hill
- 15. Discovery Partners Institute, University of Illinois System, Chicago
- 16. University of Chicago
- 17. 2i2c
- 18. North Carolina State University
- 19. University of Arizona
- 20. Indiana University
- 21. University of Colorado
- 22. Spelman College
- 23. Georgia Institute of Technology
- 24. Duke University
- 25. The Jackson Laboratory
- 26. Ohio Supercomputer Center
- 27. Software & Application Innovation Lab, Boston University
- 28. BIDS, University of California, Berkeley; CI2, University of California, San Francisco
- 29. Sloan Foundation
- 30. Oak Ridge National Laboratory
Description
The importance of data, software, and computation has long 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. And 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. Despite their importance in the academic research ecosystem, the value of DS and RSE roles is not yet widely understood or appreciated in the academic community, 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 career 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.