Civil Service Statistics data browser (2025)

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

Status Year Region_london Region_ITL1 Function_of_post Ethnicity Headcount FTE Mean_salary Median_salary
In post 2025 London London Analysis Asian 685 670 51340 47050
In post 2025 London London Analysis Black 200 195 47180 44610
In post 2025 London London Analysis Mixed 225 220 53390 50040
In post 2025 London London Analysis Other ethnicity 75 75 52340 50220
In post 2025 London London Analysis Undeclared 175 170 60010 60370
In post 2025 London London Analysis Unknown 680 665 53420 49940
In post 2025 London London Analysis White 3335 3225 60310 60310
In post 2025 London London Commercial Asian 275 270 57510 48800
In post 2025 London London Commercial Black 135 135 54230 48980
In post 2025 London London Commercial Mixed 60 60 58310 57510
In post 2025 London London Commercial Other ethnicity 25 25 [c] [c]
In post 2025 London London Commercial Undeclared 70 70 66890 62330
In post 2025 London London Commercial Unknown 210 205 54810 47660
In post 2025 London London Commercial White 1200 1175 68230 62700
In post 2025 London London Communications Asian 165 165 47580 44770
In post 2025 London London Communications Black 105 105 44530 40160
In post 2025 London London Communications Mixed 95 90 52140 48330
In post 2025 London London Communications Other ethnicity 40 40 52960 49650
In post 2025 London London Communications Undeclared 75 75 52640 49110
In post 2025 London London Communications Unknown 575 570 54290 49480
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).