Civil Service Statistics data browser (2025)

Data preview: All civil servants / Ethnicity / Region_london / Region_ITL1 / Function_of_post

Status Year Ethnicity Region_london Region_ITL1 Function_of_post Headcount FTE Mean_salary Median_salary
In post 2025 Asian London London Analysis 685 670 51340 47050
In post 2025 Asian London London Commercial 275 270 57510 48800
In post 2025 Asian London London Communications 165 165 47580 44770
In post 2025 Asian London London Counter Fraud 660 610 38410 35780
In post 2025 Asian London London Debt 165 140 31320 30070
In post 2025 Asian London London Digital and Data 1270 1255 52990 49390
In post 2025 Asian London London Finance 580 570 51100 48410
In post 2025 Asian London London Grants Management 20 20 [c] [c]
In post 2025 Asian London London Internal Audit 70 65 52600 50820
In post 2025 Asian London London Legal 795 750 53830 59800
In post 2025 Asian London London No function 9740 9175 42090 35780
In post 2025 Asian London London People 420 405 47190 42960
In post 2025 Asian London London Project Delivery 755 730 52260 48300
In post 2025 Asian London London Property 200 185 44050 39970
In post 2025 Asian London London Security 245 240 42800 41540
In post 2025 Asian London London Unknown 645 595 39120 35680
In post 2025 Asian Outside London East (England) Analysis 5 5 [c] [c]
In post 2025 Asian Outside London East (England) Commercial 10 10 [c] [c]
In post 2025 Asian Outside London East (England) Communications [c] [c] [c] [c]
In post 2025 Asian Outside London East (England) Counter Fraud 35 35 33650 34330
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

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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 2025-07-18

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.
Five 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, United Kingdom Statistics Authority, Scottish Forestry and Forest and Land Scotland.
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".
Region_ITL1 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
Function_of_post Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Of the 21 bodies under the Scottish Government, 16 did not report any functions information for their employees.
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).