Increasing computing and data storage capacity, evolving data science and artificial intelligence tools, and expanding availability of complex public health data hold promise for transforming the data and analytic capacity of government public health agencies. However, public health officials may be unable to harness these resources because the government public health workforce may lack sufficient data science skills and competencies.¹ A workforce that lacks data science skills and competencies may also not be able to optimally modernize outdated and siloed public health data infrastructures.

In 2024, the Centers for Disease Control and Prevention and the Council for State and Territorial Epidemiologists emphasized the importance of strengthening public health data science workforce capacity and suggested approaches such as recruitment/hiring, workforce exchanges with the private sector, and on-the-job training of the existing public health workforce (i.e., upskilling).^2,3 During the past several years, recruitment and hiring of data scientists into government public health had to contend with barriers such as complex application processes and the lure of lucrative private industry careers.^3,4 At least at the federal level, data science positions often require that candidates have data science-related education and degrees. Recent changes in the federal government employment and funding landscape have also introduced uncertainties and challenges.⁵

Approximately 15 000 epidemiologists and data scientists are in the state and local workforce, about 42% of whom have been in public health for 5 years or less.⁶ Among this subset of epidemiologists, about 84% have a public health degree, compared with 30% of other data scientists who have worked in public health for 5 years or fewer.⁶ Other than these general measures, few data sources are currently available to inform governmental strategic workforce planning approaches that support public health capacity-building and goal-setting. Although data from the Public Health Workforce Interests and Needs Survey provide insight into workforce training needs and general numbers of staff,^6,7 we are not aware of an evidence base for data science workforce planning, such as estimates of the number of data scientists that are needed, the number of data scientists with data science-related education and degrees who may be available to fill government public health positions, and the number of public health workforce members in other disciplines who could be upskilled to fill data science positions.

Because these numbers are not readily available, the use of novel data sources can allow incremental progress toward an evidence base for workforce planning. We provide an example. To provide an upper-bound estimate of the size of the recruitment pool of data scientists with data science-related education (but far higher than the size we expect to actually be recruitable by public health), we combined 2 existing data sources not previously used for this purpose.

To first calculate the number of recent graduates with data science degrees, we used data from the National Center for Education Statistics Postsecondary Education System (IPEDS) to calculate the number of graduates from US academic institutions who were awarded data science–related degrees in 2023.⁸ IPEDS is a system of interrelated surveys conducted annually by the US Department of Education’s National Center for Education Statistics. Every college, university, and technical and vocational institution that participates in federal student financial aid programs is mandated to report data, such as enrollment, program completion rates, graduation rates, and number and types of degrees conferred, to IPEDS. We predefined program codes (Classification of Instructional Programs [CIP])⁹ for data science disciplines that would likely qualify someone for government employment as a data scientist (eTable 1 in the Supplement). Using the CIP codes, we calculated the number of 2023 graduates who were awarded a bachelor’s, master’s, or doctoral degree.

As a proxy for interest in government public health employment among graduating public health students, we used first-destination employment data of recent public health graduates (graduation years 2015–2022) as reported by members of the Association of Schools and Programs of Public Health (ASPPH).^10,11 ASPPH collects data on the academic public health student pathway through its annual institutional reporting, which includes information about public health graduates’ first-destination employment, such as employer type (employment sector) and workplace setting (employment sector detail). We used these data because, to our knowledge, they are the only available data source on postgraduation government public health employment. We used first-destination employer type and employment setting, which included whether the workplace was in a federal, tribal, state, or local setting, to calculate percentages of public health graduates whose first-destination employment was in government public health. To allow for a range of sensitivity and specificity, we classified government public health employment in 3 ways. The broadest category included first-destination employment by a government entity or within a government setting. The second category included employment in a government setting. The narrowest category included employment in a government public health setting, such as a US Department of Health and Human Services agency or state health department. When possible, we stratified setting by federal, tribal, state, or local government public health settings. We anticipated that graduates in the ASPPH data would be more likely to be employed in government public health than those who graduated with non-public health degrees. As such, we used these data to help construct the upper bound of first-destination employment in government public health for other non-public health graduates.

To this end, we combined results from the previously mentioned calculations to estimate upper bounds of the number of recent data science graduates who may be both interested in and potentially employable by government public health. We multiplied the number of data science graduates with each degree type (from the IPEDS data) by the percentage of students whose first-destination employment was government (from the ASPPH data) across the 3 government employment categories. For percentages, we used degree-specific and setting-specific values. We used Stata version 18 (StataCorp LLC) and Microsoft Excel version 2402 (Microsoft Corp) to conduct all analyses.

In 2023, a total of 467,435 graduates were awarded a data science degree from U.S. institutions (Table 1). Of these graduates, 286,561 (61%) received a bachelor’s degree, 169,916 (36%) received a master’s degree, and 10,958 (2%) received a doctoral degree. The number of degree conferrals increased substantially, more than doubling the nearly 230 000 students that graduated with data science-related degrees in 2013.

ASPPH has first-destination outcome data for 96 578 students who graduated from an ASPPH-member school or program of public health during the 2015–2016 and 2021–2022 academic years (Table 2). Of these graduates, 23 062 (23.9%) were awarded a bachelor’s degree, 66 296 (68.6%) were awarded a master’s degree, and 7220 (8.0%) were awarded a doctoral degree. Overall, 18411 (19.1%) of 96 578 graduates received a biostatistics, epidemiology, or health informatics degree; 18 307 (24.9%) of those who graduated with a master’s or doctoral degree (n = 73 516) received a biostatistics, epidemiology, or health informatics degree.

In total, 15,201 (15.7%) of all 96,578 graduates were either employed by a government entity or worked in a government workplace setting, the broadest category. First-destination employment in a government workplace setting was reported by 12,073 (12.5%) graduates. First-destination employment in a government public health workplace setting, the most specific category, was reported by 8,045 (8.3%) graduates. Those with a bachelor’s degree tended to be employed at the local level, those with a master’s degree at the local and state levels, and those with doctoral degrees tended to be employed at the federal level.

With cautious extrapolation from the first-destination outcomes of public health graduates to interest in government public health employment among data science graduates, we estimated data science applicant pools for government public health jobs to be between nearly 29 000 and more than 57 000 (eTable 2 in the Supplement).

We combined 2 existing data sources as an initial incremental step toward establishing an evidence base to inform strategic public health workforce planning. We found a substantial number of data science-trained students graduating from US colleges and universities-more than 450 000 in 2023 alone. Based on our assumptions and calculations, we estimated that approximately 29 000 to 57 000 data science graduates might be in the government public health employment pool. Clearly, however, government public health is not drawing this level of interest from data science graduates, inside or outside public health programs.^3,4 Why is this?

It’s about money, but also more.³ Fundamentally, when attempting to hire data scientists, hiring officials in government public health face competition from lucrative private sector employers, who can often offer higher salaries, greater resources, and career advancement opportunities.^3,4 Private sector applicants report better job applicant experiences, faster hiring periods, and, increasingly, better benefits.³ The number of data scientist positions in the private sector is likely to grow, further exacerbating the competition for well-trained data scientists.¹²

We lack estimates for the number of data scientists who are needed in government public health, as well as the number of workforce members who could be upskilled to build sufficient data science capacity. Without such estimates, it is difficult to put our findings regarding the potential supply of data scientists in proper context. However, we can draw a few conclusions. We expect that our findings represent overestimates and that the actual supply of recent data science graduates potentially interested in government public health positions during the period of data collection was lower, likely substantially lower. When spread across government public health settings and considering a previously described workforce deficit¹³, the number of recently trained data scientists might not be enough to meet workforce needs.

If this is the case, efforts to strengthen data science capacity could emphasize upskilling of existing staff and consider development of data science career pathways for upskilled staff. Programs such as CDC’s Data Science Upskilling (DSU) (for CDC employees) and CSTE’s CDC-supported Data Science Team Training (DSTT) are effective upskilling models.^14,15 Upskilling can complement hiring by equipping staff with foundational data science skills and thus enabling better integration of newly hired data scientists into existing teams. The potential benefit of upskilling is reinforced by recent changes to the size of the federal workforce.

Schools and programs of public health are integral to providing current and future professionals with essential skills, including data science, to address emerging public health challenges. The upcoming 2026 Council on Education for Public Health criteria revisions present an opportunity to embed data science training into existing public health curriculum. Embedding data science, and particularly the data science skills needed in government public health, into schools and programs of public health curricula might strengthen skills among students already showing an interest in public health. Further, embedding foundational public health coursework within undergraduate core curriculum can foster a broader understanding of public health, spark early career interest, and equip students in fields like data science with foundational public health knowledge. Students and graduates who are interested in public health employment can find job postings on platforms such as Indeed, USAJobs, and public health-specific job boards.^16–18

Robust estimates of the number of data scientists required to fill government public health workforce gaps are needed to guide evidence-based decision making for workforce planning and to effectively address these gaps. We intend these findings as a step towards defining supply. Future research can refine these estimates; possible approaches include assessing the number of data science graduates who enter government public health jobs as first-destination employment or surveys of data science graduates’ interest in public health and factors that may increase their interest. Projections of demand (which can incorporate attrition to other industries and the current dynamic landscape) are also needed. If the number of estimated graduates falls short of projected demand attributable to a lack of interest or other factors, strategies such as upskilling of existing staff, strengthening the public health-specific curricula, and embedding public health education into broader undergraduate training might be needed.