| --- |
| license: mit |
| configs: |
| - config_name: postings |
| data_files: |
| - split: '2026_03' |
| path: postings/2026_03-* |
| - split: '2026_02' |
| path: postings/2026_02-* |
| - split: '2026_01' |
| path: postings/2026_01-* |
| - split: '2025_12' |
| path: postings/2025_12-* |
| - split: '2025_11' |
| path: postings/2025_11-* |
| - split: '2025_10' |
| path: postings/2025_10-* |
| - split: '2025_09' |
| path: postings/2025_09-* |
| - split: '2025_08' |
| path: postings/2025_08-* |
| - split: '2025_07' |
| path: postings/2025_07-* |
| - split: '2025_06' |
| path: postings/2025_06-* |
| - split: '2025_05' |
| path: postings/2025_05-* |
| - split: '2025_04' |
| path: postings/2025_04-* |
| - split: '2025_03' |
| path: postings/2025_03-* |
| - split: '2025_02' |
| path: postings/2025_02-* |
| - split: '2025_01' |
| path: postings/2025_01-* |
| - split: '2024_12' |
| path: postings/2024_12-* |
| - split: '2024_11' |
| path: postings/2024_11-* |
| - split: '2024_10' |
| path: postings/2024_10-* |
| - split: '2024_09' |
| path: postings/2024_09-* |
| - split: '2024_08' |
| path: postings/2024_08-* |
| - split: '2024_07' |
| path: postings/2024_07-* |
| - split: '2024_06' |
| path: postings/2024_06-* |
| - split: '2024_05' |
| path: postings/2024_05-* |
| - split: '2024_04' |
| path: postings/2024_04-* |
| - split: '2024_03' |
| path: postings/2024_03-* |
| - split: '2024_02' |
| path: postings/2024_02-* |
| - split: '2024_01' |
| path: postings/2024_01-* |
| - split: '2023_12' |
| path: postings/2023_12-* |
| - split: '2023_11' |
| path: postings/2023_11-* |
| - split: '2023_10' |
| path: postings/2023_10-* |
| - split: '2023_09' |
| path: postings/2023_09-* |
| - split: '2023_08' |
| path: postings/2023_08-* |
| - split: '2023_07' |
| path: postings/2023_07-* |
| - split: '2023_06' |
| path: postings/2023_06-* |
| - split: '2023_05' |
| path: postings/2023_05-* |
| - split: '2023_04' |
| path: postings/2023_04-* |
| - split: '2023_03' |
| path: postings/2023_03-* |
| - split: '2023_02' |
| path: postings/2023_02-* |
| - split: '2023_01' |
| path: postings/2023_01-* |
| - split: '2022_12' |
| path: postings/2022_12-* |
| - split: '2022_11' |
| path: postings/2022_11-* |
| - split: '2022_10' |
| path: postings/2022_10-* |
| - split: '2022_09' |
| path: postings/2022_09-* |
| - split: '2022_08' |
| path: postings/2022_08-* |
| - split: '2022_07' |
| path: postings/2022_07-* |
| - split: '2022_06' |
| path: postings/2022_06-* |
| - split: '2022_05' |
| path: postings/2022_05-* |
| - split: '2022_04' |
| path: postings/2022_04-* |
| - split: '2022_03' |
| path: postings/2022_03-* |
| - split: '2022_02' |
| path: postings/2022_02-* |
| - split: '2022_01' |
| path: postings/2022_01-* |
| - split: '2021_12' |
| path: postings/2021_12-* |
| - split: '2021_11' |
| path: postings/2021_11-* |
| - split: '2021_10' |
| path: postings/2021_10-* |
| - split: '2021_09' |
| path: postings/2021_09-* |
| - split: '2021_08' |
| path: postings/2021_08-* |
| - split: '2021_07' |
| path: postings/2021_07-* |
| - split: '2021_06' |
| path: postings/2021_06-* |
| - split: '2021_05' |
| path: postings/2021_05-* |
| - split: '2021_04' |
| path: postings/2021_04-* |
| - split: '2021_03' |
| path: postings/2021_03-* |
| - split: '2021_02' |
| path: postings/2021_02-* |
| - split: '2021_01' |
| path: postings/2021_01-* |
| - split: '2020_12' |
| path: postings/2020_12-* |
| - split: '2020_11' |
| path: postings/2020_11-* |
| - split: '2020_10' |
| path: postings/2020_10-* |
| - split: '2020_09' |
| path: postings/2020_09-* |
| - split: '2020_08' |
| path: postings/2020_08-* |
| - split: '2020_07' |
| path: postings/2020_07-* |
| - split: '2020_06' |
| path: postings/2020_06-* |
| - split: '2020_05' |
| path: postings/2020_05-* |
| - split: '2020_04' |
| path: postings/2020_04-* |
| - split: '2020_03' |
| path: postings/2020_03-* |
| - split: '2020_02' |
| path: postings/2020_02-* |
| - split: '2020_01' |
| path: postings/2020_01-* |
| - split: '2019_12' |
| path: postings/2019_12-* |
| - split: '2019_11' |
| path: postings/2019_11-* |
| - split: '2019_10' |
| path: postings/2019_10-* |
| - split: '2019_09' |
| path: postings/2019_09-* |
| - split: '2019_08' |
| path: postings/2019_08-* |
| - split: '2019_07' |
| path: postings/2019_07-* |
| - split: '2019_06' |
| path: postings/2019_06-* |
| - split: '2019_05' |
| path: postings/2019_05-* |
| - split: '2019_04' |
| path: postings/2019_04-* |
| - split: '2019_03' |
| path: postings/2019_03-* |
| - split: '2019_02' |
| path: postings/2019_02-* |
| - split: '2019_01' |
| path: postings/2019_01-* |
| - split: '2018_12' |
| path: postings/2018_12-* |
| - split: '2018_11' |
| path: postings/2018_11-* |
| - split: '2018_10' |
| path: postings/2018_10-* |
| - split: '2018_09' |
| path: postings/2018_09-* |
| - split: '2018_08' |
| path: postings/2018_08-* |
| - split: '2018_07' |
| path: postings/2018_07-* |
| - split: '2018_06' |
| path: postings/2018_06-* |
| - split: '2018_05' |
| path: postings/2018_05-* |
| - split: '2018_04' |
| path: postings/2018_04-* |
| - split: '2018_03' |
| path: postings/2018_03-* |
| - split: '2018_02' |
| path: postings/2018_02-* |
| - split: '2018_01' |
| path: postings/2018_01-* |
| - split: '2017_12' |
| path: postings/2017_12-* |
| - split: '2017_11' |
| path: postings/2017_11-* |
| - split: '2017_10' |
| path: postings/2017_10-* |
| - split: '2017_09' |
| path: postings/2017_09-* |
| - split: '2017_08' |
| path: postings/2017_08-* |
| - split: '2017_07' |
| path: postings/2017_07-* |
| - split: '2017_06' |
| path: postings/2017_06-* |
| - split: '2017_05' |
| path: postings/2017_05-* |
| - split: '2017_04' |
| path: postings/2017_04-* |
| - split: '2017_03' |
| path: postings/2017_03-* |
| - split: '2017_02' |
| path: postings/2017_02-* |
| - split: '2017_01' |
| path: postings/2017_01-* |
| dataset_info: |
| config_name: postings |
| features: |
| - name: usajobsControlNumber |
| dtype: string |
| - name: wage_min |
| dtype: string |
| - name: wage_max |
| dtype: string |
| - name: wage_freq |
| dtype: string |
| - name: title_code |
| dtype: string |
| - name: title_score |
| dtype: float32 |
| - name: title_value |
| dtype: float32 |
| - name: title_features |
| dtype: string |
| - name: flesch_kincaid |
| dtype: float32 |
| - name: CitizenshipReq |
| dtype: bool |
| - name: GovContract |
| dtype: bool |
| - name: VisaExclude |
| dtype: bool |
| - name: VisaInclude |
| dtype: bool |
| - name: WorkAuthReq |
| dtype: bool |
| - name: driverslicense |
| dtype: bool |
| - name: ind_contractor |
| dtype: bool |
| - name: proflicenses |
| dtype: bool |
| - name: wfh |
| dtype: bool |
| - name: yesunion |
| dtype: bool |
| - name: tasks |
| dtype: string |
| - name: skills |
| dtype: string |
| - name: concepts |
| dtype: string |
| - name: ai_codes |
| dtype: string |
| - name: ai_matches |
| dtype: int8 |
| - name: ai_score |
| dtype: float32 |
| - name: ai_selection_score |
| dtype: string |
| - name: ai_match_score |
| dtype: string |
| - name: ai_score_v2 |
| dtype: float32 |
| - name: ai_strict_score |
| dtype: float32 |
| - name: ai_lenient_score |
| dtype: float32 |
| splits: |
| - name: '2026_03' |
| num_bytes: 21976916 |
| num_examples: 14145 |
| - name: '2026_02' |
| num_bytes: 27413202 |
| num_examples: 17673 |
| - name: '2026_01' |
| num_bytes: 22907821 |
| num_examples: 14762 |
| - name: '2025_12' |
| num_bytes: 20313366 |
| num_examples: 12995 |
| - name: '2025_11' |
| num_bytes: 17712056 |
| num_examples: 11129 |
| - name: '2025_10' |
| num_bytes: 21202189 |
| num_examples: 13312 |
| - name: '2025_09' |
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| num_examples: 14080 |
| - name: '2025_08' |
| num_bytes: 24269948 |
| num_examples: 15614 |
| - name: '2025_07' |
| num_bytes: 23168222 |
| num_examples: 14722 |
| - name: '2025_06' |
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| - name: '2025_05' |
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| - name: '2025_04' |
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| - name: '2025_03' |
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| - name: '2025_02' |
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| - name: '2025_01' |
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| - name: '2024_12' |
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| - name: '2024_11' |
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| - name: '2024_10' |
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| - name: '2024_09' |
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| - name: '2022_05' |
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| - name: '2022_04' |
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| - name: '2022_03' |
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| - name: '2022_02' |
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| num_examples: 35755 |
| - name: '2022_01' |
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| num_examples: 34487 |
| - name: '2021_12' |
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| - name: '2021_11' |
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| - name: '2021_09' |
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| - name: '2021_08' |
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| - name: '2021_07' |
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| - name: '2021_05' |
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| - name: '2021_04' |
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| num_examples: 31076 |
| - name: '2021_03' |
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| - name: '2021_02' |
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| num_examples: 27291 |
| - name: '2021_01' |
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| num_examples: 24976 |
| - name: '2020_12' |
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| - name: '2020_11' |
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| num_examples: 24289 |
| - name: '2020_10' |
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| num_examples: 28540 |
| - name: '2020_09' |
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| - name: '2020_08' |
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| - name: '2020_07' |
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| - name: '2017_08' |
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| - name: '2017_07' |
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| - name: '2017_06' |
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| - name: '2017_05' |
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| num_examples: 22764 |
| - name: '2017_04' |
| num_bytes: 25594947 |
| num_examples: 18623 |
| - name: '2017_03' |
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| num_examples: 20060 |
| - name: '2017_02' |
| num_bytes: 9124247 |
| num_examples: 6369 |
| - name: '2017_01' |
| num_bytes: 3128458 |
| num_examples: 2247 |
| download_size: 808842875 |
| dataset_size: 3876305595 |
| --- |
| |
| # USAJOBS Coded Dataset (2017-01 to 2026-03) |
|
|
| ## Dataset Description |
| The **USAJOBS Dataset** is a comprehensive collection of federal job postings from January 2017 through March 2026. This dataset includes full-text job descriptions, and structured metadata (job title and employer). |
|
|
| In this *coded* version, we presented the structured features assigned to each of the postings (by `usajobsControlNumber`), as produced by [JAAT](https://github.com/Job-Ad-Research-at-QSB-LUC/JAAT). |
|
|
| ## Dataset Structure |
|
|
| ### Splits |
| This dataset is organized by **month** to allow for easy time-series analysis without requiring the user to download the entire multi-year corpus. |
|
|
| * **Monthly Splits:** Format `YYYY_MM` (e.g., `2017_01`, `2025_12`). |
|
|
| ### Data Fields |
| Each split contains the following fields: |
|
|
| * `usajobsControlNumber`: Unique identifier code for the USAJOBS job posting. |
| * `wage_min`: Minimum salary detected by `WageExtract`. |
| * `wage_max`: Maximum salary detected by `WageExtract`. |
| * `wage_freq`: Frequency of the wage (e.g., hourly, annually) by `WageExtract`. |
| * `title_code`: O*NET occupation code (`TitleMatch`). |
| * `title_score`: Confidence score of the above. |
| * `title_value`: Extracted numerical value of the title, based on seniority and experience (`TitleMatch`). |
| * `title_features`: Categorical features of the title, if any (`TitleMatch`). |
| * `flesch_kincaid`: Readability score measuring the complexity of the job posting text. |
| * `CitizenshipReq`: Boolean flag indicating if United States citizenship is mandatory. |
| * `GovContract`: Boolean flag indicating if the position involves government contract work. |
| * `VisaExclude`: Boolean flag indicating if specific visa types are barred from applying. |
| * `VisaInclude`: Boolean flag indicating if visa sponsorship options are explicitly included. |
| * `WorkAuthReq`: Boolean flag indicating if valid proof of work authorization is requested. |
| * `driverslicense`: Boolean flag indicating if a valid driver's license is required. |
| * `ind_contractor`: Boolean flag indicating if the job operates as an independent contractor role. |
| * `proflicenses`: Boolean flag indicating if specialized professional licenses are required. |
| * `wfh`: Boolean flag indicating if the position offers work-from-home or remote options. |
| * `yesunion`: Boolean flag indicating if the position belongs to a labor union. |
| * `tasks`: Text string capturing the coded O*NET tasks, extracted by `TaskMatch`. |
| * `skills`: Text string capturing the ESCO skills extracted by `SkillMatch`. |
| * `concepts`: Text string of the custom-extracted concepts extracted with `ConceptSearch`. |
| * `ai_codes`: AI taxonomy codes extracted by `AIMatch` (beta). |
| * `ai_matches`: How many AI codes were extracted. |
| * `ai_score`: Overall AI score, following a custom scoring scheme. |
| * `ai_selection_score`: Extraction score representing confidence that the statement is AI-related (;-delimited list of scores). |
| * `ai_match_score`: Same as the above, but now for matching confidence. |
| * `ai_score_v2`: Updated version 2 of our custom AI scoring. |
| * `ai_strict_score`: AI score representing only frontier AI work. |
| * `ai_lenient_score`: AI score that is more lenient in the defintion of "AI". |
|
|
| ## |
|
|
| If you find this dataset useful or utilize it for your work, please consider citing our working paper: |
|
|
| ``` |
| @article{meisenbacher2025extracting, |
| title={Extracting O* NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data}, |
| author={Meisenbacher, Stephen and Nestorov, Svetlozar and Norlander, Peter}, |
| year={2025} |
| } |
| ``` |
