| Status | Year | Region_london | Ethnicity | Sex | Function_of_post | Headcount | FTE | Mean_salary | Median_salary |
|---|---|---|---|---|---|---|---|---|---|
| In post | 2024 | London | Asian | Female | Analysis | 265 | 255 | 48440 | 45430 |
| In post | 2024 | London | Asian | Female | Commercial | 120 | 115 | 52070 | 45660 |
| In post | 2024 | London | Asian | Female | Communications | 105 | 105 | 44620 | 41580 |
| In post | 2024 | London | Asian | Female | Counter Fraud | 380 | 345 | 35990 | 33980 |
| In post | 2024 | London | Asian | Female | Debt | 90 | 75 | 29710 | 28610 |
| In post | 2024 | London | Asian | Female | Digital, Data & Technology | 460 | 450 | 48090 | 45600 |
| In post | 2024 | London | Asian | Female | Finance | 285 | 275 | 47740 | 45870 |
| In post | 2024 | London | Asian | Female | Grants Management | 10 | 10 | [c] | [c] |
| In post | 2024 | London | Asian | Female | Human Resources | 310 | 295 | 44540 | 40910 |
| In post | 2024 | London | Asian | Female | Internal Audit | 35 | 35 | 48040 | 48400 |
| In post | 2024 | London | Asian | Female | Legal | 575 | 535 | 50400 | 56550 |
| In post | 2024 | London | Asian | Female | No function | 5630 | 5180 | 39720 | 34330 |
| In post | 2024 | London | Asian | Female | Project Delivery | 420 | 400 | 49750 | 45000 |
| In post | 2024 | London | Asian | Female | Property | 115 | 105 | 39890 | 37240 |
| In post | 2024 | London | Asian | Female | Security | 105 | 100 | 42500 | 39540 |
| In post | 2024 | London | Asian | Female | Unknown | 420 | 380 | 38620 | 33980 |
| In post | 2024 | London | Asian | Male | Analysis | 260 | 260 | 47640 | 43720 |
| In post | 2024 | London | Asian | Male | Commercial | 115 | 115 | 54950 | 47670 |
| In post | 2024 | London | Asian | Male | Communications | 45 | 45 | 46500 | 42810 |
| In post | 2024 | London | Asian | Male | Counter Fraud | 255 | 250 | 37700 | 34270 |
About: The Civil Service Statistics data browser is a pilot project by Cabinet Office to provide access to more detailed data on the Civil Service workforce from the Annual Civil Service Employment Survey. We welcome feedback or comments on this project, which can be addressed to civilservicestatistics@cabinetoffice.gov.uk
Notes: Summary figures are suppressed when information relates to less than 5 civil servants for FTE or Headcount, and less than 10 civil servants for median and mean salary (shown as [c]). Zero responses and salaries for less than 30 civil servants have been suppressed for GPDR special category data. FTE figures are not shown for entrants or leavers due to data quality concerns for these groups. Figures are rounded to the nearest 5, or £10 as appropriate.
Data source: All figures are aggregated from the Cabinet Office Annual Civil Service Employment Survey collection.
Version: Generated on 2024-07-25
| Data column | Description |
|---|---|
| Status | Employment status of the civil servants. |
| In post - includes staff that were in post on the reference date (31 March). | |
| New entrant CS - includes new entrants to the Civil Service over the year (1 April to 31 March). | |
| Leaver CS - includes leavers from the Civil Service over the year (1 April to 31 March). This includes employees who have an Unknown leaving cause. | |
| Leaver Dept. - includes leavers from the department over the year (1 April to 31 March), who did not leave the Civil Service. | |
| Four organisations do not report when their employees first entered the Civil Service and so entrants data for these organisations is not available . These are as follows: Foreign Commonwealth and Development Office (excl. agencies), Foreign Commonwealth and Development Office Services, Scottish Forestry and Forest and Land Scotland. A further three organisations also could not provide entrants data in 2021. These are as follows: Department for International Development, Foreign and Commonwealth Office (excl. agencies) and Royal Fleet Auxiliary. | |
| Year | Year of data collection (as at 31 March). |
| Region_london | Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard. |
| Region_london groups the ITL classifications into "London", "Outside London": all UK regions excluding London, "Overseas", and "Unknown". | |
| Function_of_post | Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have. |
| Welsh Government and Royal Fleet Auxiliary did not report any functions information for their employees. | |
| Of the 20 bodies under the Scottish Government, 16 did not report any functions information for their employees. | |
| Sex | Self reported sex. |
| "Unknown" accounts for employees who were recorded with an unknown sex. | |
| Ethnicity | Self reported ethnicity. "Undeclared" accounts for employees who have actively declared that they do not want to disclose their ethnicity and "Unknown" accounts for employees who have not made an active declaration about their ethnicity. |
| Headcount | Total number of civil servants (rounded to nearest 5). |
| FTE | Total full-time equivalent (FTE) employment numbers (rounded to nearest 5). |
| FTE figures are not shown for entrants or leavers due to data quality concerns for these groups. | |
| Mean_salary | Average salary (mean, rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries. |
| These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown). | |
| Median_salary | Median salary (rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries. |
| These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown). |