Civil Service Statistics data browser (2025)

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

Status Year Region_london Ethnicity Region_ITL1 Responsibility_level_ungrouped Headcount FTE Mean_salary Median_salary
In post 2025 London Asian London AA 220 195 28830 27800
In post 2025 London Asian London AO 2080 1845 30370 30070
In post 2025 London Asian London EO 4800 4465 34780 35150
In post 2025 London Asian London G6 800 775 78510 77500
In post 2025 London Asian London G7 2360 2305 64090 62990
In post 2025 London Asian London HEO 3380 3275 40700 41550
In post 2025 London Asian London SCS level 250 240 103210 91620
In post 2025 London Asian London SEO 2525 2470 48880 48730
In post 2025 London Asian London Unknown 275 260 35670 31350
In post 2025 London Black London AA 335 315 30490 31660
In post 2025 London Black London AO 2080 1930 32420 30750
In post 2025 London Black London EO 3500 3320 35000 35680
In post 2025 London Black London G6 240 235 77430 77220
In post 2025 London Black London G7 1120 1100 64190 62960
In post 2025 London Black London HEO 2040 1995 41030 41550
In post 2025 London Black London SCS level 70 70 99830 91000
In post 2025 London Black London SEO 1410 1390 49130 49000
In post 2025 London Black London Unknown 770 735 37550 35900
In post 2025 London Mixed London AA 45 45 30120 28050
In post 2025 London Mixed London AO 355 335 32350 30580
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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).
Responsibility_level_ungrouped With the exception of the centrally managed Senior Civil Service, government departments have delegated pay and grading. For statistical purposes departments are asked to map their grades to a common framework by responsibility level.
This table shows staff in their substantive responsibility level unless on temporary promotion in which case staff are recorded at the higher responsibility level.
Responsibility_level_ungrouped shows the mapped grades at a higher level of detail, however not all Government Departments / bodies have distinct grades that map exactly to these levels so figures should be considered as approximations and treated with caution.
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.
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).