Abstract
Objectives:
In 2024, the Centers for Disease Control and Prevention and the Council of State and Territorial Epidemiologists suggested approaches, including upskilling and recruitment/hiring, to strengthen the workforce capacity in public health data science. We estimated the number of recently graduated data scientists who might be eligible for and potentially hirable into government public health jobs as a step toward filling data gaps in workforce planning.
Methods:
We used data from the National Center for Education Statistics to calculate the number of data science graduates in 2023. As a proxy for interest in government public health among graduates, we used data from the Association of Schools and Programs of Public Health (graduation years 2015-2022). We multiplied the number of data science graduates from US academic institutions (from National Center for Education Statistics data) by the percentage of public health graduates who entered government public health employment (from Association of Schools and Programs of Public Health data) to estimate the number of data science graduates who might be eligible for and interested in government public health employment.
Results:
In 2023, 467 435 graduates were awarded a data science degree from a US institution. Depending on the government employment criteria, 8.3% to 15.7% of 96 578 public health graduates reported first-destination employment in government public health. The total number of data science graduates who might be eligible for and interested in government public health employment ranged from nearly 29 000 to >57 000.
Conclusions:
These data contribute to the evidence base for public health workforce planning but are likely to be overestimates of supply. If the estimated supply of data scientists falls short of demand projections, staff data science upskilling and changes to academic curricula could be emphasized.
Keywords: data scientist, data science, public health, workforce, government
Increasing computing and data storage capacity, evolving data science and artificial intelligence tools, and expanding the 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 (CDC) and the Council of 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 (ie, 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. 6 Among this subset of epidemiologists, about 84% have a public health degree, as compared with 30% of other data scientists who have worked in public health for ≤5 years. 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 (1) estimates of the number of data scientists that are needed, (2) the number of data scientists with data science–related education and degrees who may be available to fill government public health positions, and (3) 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 that we expect to actually be recruitable by public health), we combined 2 existing data sources not previously used for this purpose.
Methods
To first calculate the number of recent graduates with data science degrees, we used data from the National Center for Education Statistics’ Integrated Postsecondary Education Data 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 to IPEDS, such as enrollment, program completion rates, graduation rates, and number and types of degrees conferred. We predefined program codes for data science disciplines that would likely qualify someone for government employment as a data scientist (eTable 1 in the Supplement). Using the Classification of Instructional Programs codes, 9 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 the 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 the 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 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- and setting-specific values. We used Stata version 18 (StataCorp LLC) and Microsoft Excel version 2402 (Microsoft Corp) to conduct all analyses.
Ethical Considerations
This study received a non–human subjects research determination by CDC’s Human Research Protections Office (August 2024) because it used available data without personal identifiers and because of the lack of interaction with or collection of identifiable information about human subjects (project ID 0900f3eb8240cfd0). This activity did not involve primary data collection; as such, informed consent was not required.
Results
In 2023, a total of 467 435 graduates were awarded a data science degree from a US institution (Table 1). Of these graduates, 286 561 (61.3%) received a bachelor’s degree, 169 916 (36.4%) a master’s degree, and 10 958 (2.3%) a doctoral degree. The number of degree conferrals increased substantially, more than doubling the nearly 230 000 students who graduated with data science–related degrees in 2013.
Table 1.
Number and types of data science graduates by degree, National Center for Education Statistics postsecondary education system, graduating years 2013-2023, United States a
| Year | Bachelor’s degree | Master’s degree | Doctoral degree | Total |
|---|---|---|---|---|
| 2013 | 162 064 | 58 919 | 6922 | 227 905 |
| 2014 | 173 261 | 62 428 | 7281 | 242 970 |
| 2015 | 184 951 | 71 431 | 7281 | 263 663 |
| 2016 | 196 607 | 83 983 | 7358 | 287 948 |
| 2017 | 210 202 | 94 183 | 7836 | 312 221 |
| 2018 | 225 373 | 100 308 | 8277 | 333 958 |
| 2019 | 243 724 | 105 971 | 8649 | 358 344 |
| 2020 | 261 895 | 117 689 | 9221 | 388 805 |
| 2021 | 278 060 | 127 606 | 9421 | 415 087 |
| 2022 | 283 590 | 131 321 | 10 596 | 425 507 |
| 2023 | 286 561 | 169 916 | 10 958 | 467 435 |
Refer to Supplemental Table 1 for definition of programs included in these estimates. Data source: National Center for Education Statistics, Integrated Postsecondary Education Data System.7,10
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%) a master’s degree, and 7220 (8.0%) a doctoral degree. Overall, 18 411 (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.
Table 2.
Number of public health graduates by degree and known first-destination employment, Association of Schools and Programs of Public Health members, graduating years 2015-2022, United States
| No. (%) a | ||||
|---|---|---|---|---|
| First-destination employment | Bachelor’s degree (n = 23 062) | Master’s degree (n = 66 296) | Doctoral degree (n = 7220) | Total (N = 96 578) |
| Government employer or workplace setting | 1966 (8.5) | 12 091 (18.2) | 1144 (15.8) | 15 201 (15.7) |
| All other employers or settings | 21 096 (91.5) | 54 205 (81.8) | 6076 (84.2) | 81 377 (84.3) |
| Government workplace setting | 1602 (6.9) | 9582 (14.5) | 889 (12.3) | 12 073 (12.5) |
| Federal | 444 (1.9) | 2570 (3.9) | 507 (7.0) | 3521 (3.6) |
| Tribal | 9 (0.0) | 58 (0.1) | 7 (0.1) | 74 (0.1) |
| State | 455 (2.0) | 3534 (5.3) | 234 (3.2) | 4223 (4.4) |
| Local | 694 (3.0) | 3420 (5.2) | 141 (2.0) | 4255 (4.4) |
| All other settings | 21 460 (93.1) | 56 714 (85.5) | 6331 (87.7) | 84 505 (87.5) |
| Government public health workplace setting | 869 (3.8) | 6572 (9.9) | 604 (8.4) | 8045 (8.3) |
| HHS agency | 192 (0.8) | 1363 (2.1) | 316 (4.4) | 1871 (1.9) |
| Tribal government | 9 (0.0) | 58 (0.1) | 7 (0.1) | 74 (0.1) |
| State health department | 234 (1.0) | 2484 (3.7) | 174 (2.4) | 2892 (3.0) |
| Local health department | 434 (1.9) | 2667 (4.0) | 107 (1.5) | 3208 (3.3) |
| All other settings | 22 193 (96.2) | 59 724 (90.1) | 6616 (91.6) | 88 533 (91.7) |
Abbreviation: HHS, US Department of Health and Human Services.
Percentages in the cells of these columns were used for results in Supplemental Table 2. Data source: Association of Schools and Programs of Public Health. 9
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 (Table 2). 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 8045 (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 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 >57 000 (eTable 2 in the Supplement).
Discussion
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, >450 000 in 2023 alone. Based on our assumptions and calculations, 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 is 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 better 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 and 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 about 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 who were 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 deficit, 13 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 (for CDC employees) and the Council of State and Territorial Epidemiologists’ CDC-supported Data Science Team Training 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 equipping current and future public health 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, particularly the data science skills needed in government public health, into schools and programs of public health curricula might strengthen skills among students who already show an interest in public health. Furthermore, embedding foundational public health coursework within an undergraduate core curriculum can foster a broader understanding of public health, spark early career interest, and equip students in fields such as 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
Limitations
Our methods and analyses had several limitations. First, we excluded non–US data science graduates and people with data science skills who lacked a data science degree. Although inclusion of these people would increase supply estimates, some of them might be ineligible for government employment because of immigration, work authorization, and hiring policies. Second, we did not consider changes over time in first-destination employment data because interest in and availability of public health employment are anticipated to change over time. Third, availability of public data such as IPEDS for future updated estimates might be subject to changes in government employment and funding.
Conclusions
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 for these findings to be a step toward 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 conducting 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 public health–specific curricula, and embedding public health education into broader undergraduate training might be needed.
Supplemental Material
Supplemental material, sj-docx-1-phr-10.1177_00333549261427670 for Estimating the Potential Supply of Newly Trained Data Scientists for Government Public Health Employment by Robert D. Kirkcaldy, Hunter Doyle, Sarah Gusman, Emily Burke, Kyle T. Bernstein and Jonathon P. Leider in Public Health Reports®
Footnotes
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Robert D. Kirkcaldy, MD, MPH 
https://orcid.org/0000-0002-1749-4647
Hunter Doyle, MPH
https://orcid.org/0009-0005-0571-4365
Emily Burke, EdD, MPH, CPH
https://orcid.org/0000-0001-5534-5100
Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Supplemental Material: Supplemental material for this article is available online. The authors have provided these supplemental materials to give readers additional information about their work. These materials have not been edited or formatted by Public Health Reports’s scientific editors and, thus, may not conform to the guidelines of the AMA Manual of Style, 11th Edition.
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Associated Data
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Supplementary Materials
Supplemental material, sj-docx-1-phr-10.1177_00333549261427670 for Estimating the Potential Supply of Newly Trained Data Scientists for Government Public Health Employment by Robert D. Kirkcaldy, Hunter Doyle, Sarah Gusman, Emily Burke, Kyle T. Bernstein and Jonathon P. Leider in Public Health Reports®