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Statistical software skills for master's-level jobs in epidemiology: an analysis of 15 years of job posting data
Emily Goldmann1, Ruby Barnard-Mayers1, M Maria Glymour1
1Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, United States.
Abstract:
Developing competency in statistical software is a core component of master's-level epidemiology training, but selecting a software package to prioritize in courses is a challenge. We used data from Lightcast to identify unique US job postings from January 2010-December 2024 with a preference or requirement for a master's degree and "epidemiology" as a keyword to identify the most frequently mentioned specific statistical software skills overall and by industry. Of the 15 757 postings from 2024, SAS® Software was mentioned most frequently (26%), followed by R (22%), SQL (15%), Excel (14%), and Python (14%). SAS® mentions decreased in proportion from 40% in 2021 to 26% in 2024, while from 2010 to 2024 mentions increased for R (3% to 22%), Python (0% to 14%), and SQL (6% to 15%). In 2024, SAS® was the most commonly mentioned software in insurance (60%), government (28%), and hospital (17%) postings, R in pharmaceutical (21%) and academic (21%) postings. Postings commonly mentioned more than one statistical software package. While SAS® remains a commonly desired statistical software skill, R is increasing in relevance quickly, especially in key industries that employ master's-level epidemiologists. Students may benefit from training focused on versatility and adaptation to emerging trends.
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