Li, D., & Milonas, E., & Zhang, Q. (2024, June), Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47871

\bibitem{asee_peer_47871}
  Li, D., \& Milonas, E., \& Zhang, Q. (2024, June), \emph{Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  https://peer.asee.org/47871

Duo Li, Elizabeth Milonas, and Qiping Zhang.  "Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/47871 Internet.  30 Jul, 2024

\bibitem{asee_peer_47871}
  Duo Li, Elizabeth Milonas, and Qiping Zhang.
  "Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/47871 Internet.  30 Jul, 2024

@INPROCEEDINGS{asee_peer_47871
author = "Duo Li, Elizabeth Milonas, and Qiping Zhang"
title = "Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/47871}
}

TY  - CPAPER
AB  - Background: 
The increased use of Data Science technologies, particularly artificial intelligence and machine learning, has caused an increase in demand for skilled Data Science professionals [1,2,3]. This demand is driven by the rising dependence of businesses on these technologies to inform strategic decisions [1,2,3]. The Data Science domain is multidisciplinary, encompassing skill sets, including statistics, business, and computer science [3]. Data Science professionals are expected to master this diverse skill set [3]. However, the Data Science domain is constantly and rapidly changing as new technologies are incorporated into the field [3]. This ever-evolving landscape poses a difficult challenge to universities tasked with educating the next generation of data scientists. To adequately prepare students for the dynamic demands of the Data Science domain, the data science competencies taught in university courses must align with the required skills demanded by industry. 
Goal: 
This study analyzes the alignment between Data Science competencies taught in 136 undergraduate Data Science programs across the United States [4] and the skills required for full-time, entry-level undergraduate degree Data Science jobs as listed on Indeed. 
Research Questions: 
The research questions answered as a result of this study are: 1) Do the Data Science competencies taught in undergraduate programs align with the required skills for entry-level, full-time Data Science jobs?  2) Does such alignment vary by industry? 
Method: 
Dataset: Data was crawled from the Indeed website to identify full-time, entry-level, undergraduate degree Data Science job postings and their required job skills. The job skills were analyzed and compared to the Data Science competencies taught in 136 undergraduate Data Science programs across the United States [4]. 
Findings and Conclusion: 
The initial findings suggest that the majority of current undergraduate data science programs effectively prepare students to meet the minimum job requirements, regardless of the industry. However, additional knowledge and skills are required for students to achieve full competency in job responsibilities. Jobs requiring specific domain expertise may require students to pursue advanced studies or degrees to satisfy these specific requirements.   

Work Cited
[1] S. Gottipati, K. J. Shim, and S. Sahoo, "Glassdoor Job Description Analytics–Analyzing Data Science Professional Roles and Skills," in 2021 IEEE Global Engineering Education Conference (EDUCON), pp. 1329-1336, IEEE, 2021.
 [2] B. A. Quismorio, M. A. D. Pasquin, and C. S. Tayco, "Assessing the alignment of Philippine higher education with the emerging demands for data science and analytics workforce," PIDS Discussion Paper Series, 2019, no. 2019-34.
 [3] M. Almgerbi, A. De Mauro, A. Kahlawi, and V. Poggioni, "A systematic review of data analytics job requirements and online-courses," Journal of Computer Information Systems, vol. 62, no. 2, pp. 422-434, 2022.
 [4] Milonas, E., Zhang, Q., & Li, D. (2022, August). Do Undergraduate Data Science Program Competencies Vary by College Rankings? Paper presented at the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. [Online]. Available: https://peer.asee.org/41153
 
 


AU  - Duo Li
AU  - Elizabeth Milonas
AU  - Qiping Zhang
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Preparing Undergraduate Data Scientists for Success in the Workplace: Aligning Competencies with Job Requirements
UR  - https://peer.asee.org/47871
ER  -