Clinical Data Managers
Computer and Mathematical Occupations- O*NET-SOC code
- 15-2051.02
Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends.
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.461
0.000Range of values carried here0.745Group-level value
Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.57
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Show 12 hidden tasks21 rated tasks · 21 tasks with β ≥ 0.5 (100.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- All rated tasks are in the O*NET 31.0 task list.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 30.2) | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare data analysis listings and activity, performance, or progress reports.15-2051.02 | 0.070035.0 | 0.140035.0 |
Prepare appropriate formatting to data sets as requested.15-2051.02 | 0.060030.0 | 0.150037.5 |
Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency.15-2051.02 | 0.040020.0 | 0.01002.5 |
Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.15-2051.02 | 0.01005.0 | 0.050012.5 |
Analyze clinical data using appropriate statistical tools.15-2051.02 | 0.01005.0 | 0.01002.5 |
Write work instruction manuals, data capture guidelines, or standard operating procedures.15-2051.02 | 0.01005.0 | 0.00000.0 |
Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.15-2051.02 | 0.00000.0 | 0.01002.5 |
Monitor work productivity or quality to ensure compliance with standard operating procedures. | —0 | 0.02005.0 |
Process clinical data, including receipt, entry, verification, or filing of information. | —0 | 0.01002.5 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Prepare appropriate formatting to data sets as requested.O*NET Task ID 16268 | 1.0 |
Develop technical specifications for data management programming and communicate needs to information technology staff.O*NET Task ID 16270 | 1.0 |
Develop or select specific software programs for various research scenarios.O*NET Task ID 16271 | 1.0 |
Write work instruction manuals, data capture guidelines, or standard operating procedures.O*NET Task ID 16273 | 1.0 |
Design and validate clinical databases, including designing or testing logic checks.O*NET Task ID 16281 | 1.0 |
Design forms for receiving, processing, or tracking data.O*NET Task ID 16286 | 1.0 |
Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.O*NET Task ID 16266 | 0.5 |
Provide support and information to functional areas such as marketing, clinical monitoring, and medical affairs.O*NET Task ID 16267 | 0.5 |
Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency.O*NET Task ID 16269 | 0.5 |
Contribute to the compilation, organization, and production of protocols, clinical study reports, regulatory submissions, or other controlled documentation.O*NET Task ID 16272 | 0.5 |
Track the flow of work forms, including in-house data flow or electronic forms transfer.O*NET Task ID 16274 | 0.5 |
Train staff on technical procedures or software program usage.O*NET Task ID 16275 | 0.5 |
Supervise the work of data management project staff.O*NET Task ID 16276 | 0.5 |
Prepare data analysis listings and activity, performance, or progress reports.O*NET Task ID 16277 | 0.5 |
Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.O*NET Task ID 16278 | 0.5 |
Monitor work productivity or quality to ensure compliance with standard operating procedures.O*NET Task ID 16279 | 0.5 |
Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.O*NET Task ID 16280 | 0.5 |
Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols.O*NET Task ID 16282 | 0.5 |
Analyze clinical data using appropriate statistical tools.O*NET Task ID 16283 | 0.5 |
Process clinical data, including receipt, entry, verification, or filing of information.O*NET Task ID 16284 | 0.5 |
Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes.O*NET Task ID 16285 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (21)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices. | Core |
| Prepare appropriate formatting to data sets as requested. | Core |
| Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency. | Core |
| Develop technical specifications for data management programming and communicate needs to information technology staff. | Core |
| Contribute to the compilation, organization, and production of protocols, clinical study reports, regulatory submissions, or other controlled documentation. | Core |
| Write work instruction manuals, data capture guidelines, or standard operating procedures. | Core |
| Track the flow of work forms, including in-house data flow or electronic forms transfer. | Core |
| Train staff on technical procedures or software program usage. | Core |
| Supervise the work of data management project staff. | Core |
| Prepare data analysis listings and activity, performance, or progress reports. | Core |
| Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data. | Core |
| Monitor work productivity or quality to ensure compliance with standard operating procedures. | Core |
| Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems. | Core |
| Design and validate clinical databases, including designing or testing logic checks. | Core |
| Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols. | Core |
| Analyze clinical data using appropriate statistical tools. | Core |
| Process clinical data, including receipt, entry, verification, or filing of information. | Core |
| Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes. | Core |
| Design forms for receiving, processing, or tracking data. | Core |
| Provide support and information to functional areas such as marketing, clinical monitoring, and medical affairs. | Supplemental |
| Develop or select specific software programs for various research scenarios. | Supplemental |
0.00/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
None of this occupation's O*NET 29.3 tasks is classified as a physical task.
Occupation information
Employment outlook (BLS)
Values for the whole SOC 15-2051 group (Data scientists), not for this O*NET occupation alone.
- Employment, 2025
- 276K
- Projected employment, 2035
- 371K
- Change (2025–35)
- +34.6%
- Median annual wage, 2025
- $120,230
- Typical education needed for entry
- Bachelor's degree
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 22412 | 데이터베이스 관리 및 운영자 | Related, not a match | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 3314Statistical, Mathematical and Related Associate Professionals
The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.
Statistical, mathematical and related associate professionals assist in planning the collection, processing and presentation of statistical, mathematical or actuarial data and in carrying out these operations, usually working under the guidance of statisticians, mathematicians and actuaries.
Tasks
- (a) assisting in planning and performing statistical, mathematical, actuarial and related calculations;
- (b) preparing detailed estimates of quantities and costs of materials and labour required for statistical census and survey operations;
- (c) performing technical tasks connected with establishing, maintaining and using registers and sampling frames for census and survey operations;
- (d) performing technical tasks connected with data collection and quality control operations in censuses and surveys;
- (e) using standard computer software packages to perform mathematical, actuarial, statistical, accounting and related calculations;
- (f) preparing statistical, mathematical, actuarial, accounting and other results for presentation in graphical or tabular form;
- (g) applying knowledge of statistical, mathematical, actuarial, accounting and related principles and practices in order to identify and solve problems arising in the course of their work;
- (h) supervising the work of statistical clerks.
Example occupations
Actuarial assistant · Mathematical assistant · Statistical assistant
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- clinical informatics managerESCO 1342.1Overlapping, not the same
Clinical informatics managers oversee the daily operations of information systems used in a medical institutions. They also carry out research, using their understanding of clinical practices to find ways to improve healthcare services.
- medical records managerESCO 3252.2Overlapping, not the same
Medical records managers are responsible for managing activities of medical records units which maintain and secure patient data. They supervise, oversee and train employees while implementing medical department policies.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| H1223 | Coordinateur / Coordinatrice d'études cliniques en industrie pharmaceutique | Related, not a matchprovisional |
| K2403 | Biostatisticien / Biostatisticienne | Related, not a matchprovisional |
| M1617 | Médecin responsable de la Documentation et de l'Information Médicale (Médecin responsable DIM) | Related, not a matchprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 2721 | Diseñadores y administradores de bases de datos | Related, not a match |
| 3322 | Técnicos superiores en documentación sanitaria | Related, not a match |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 73342 | Berufe in der medizinischen Dokumentation - fachlich ausgerichtete Tätigkeiten | This occupation is narrower |
| 41114 | Berufe in der Statistik - hoch komplexe Tätigkeiten | Related, not a match |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 109 | その他の情報処理・通信技術者 | Related, not a match |
| 259 | その他の一般事務従事者 | Related, not a match |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources