Civil Service Statistics data browser (2025)

Data preview: All civil servants / Sex / Profession_of_post / Region_london / Region_ITL1

Status Year Sex Profession_of_post Region_london Region_ITL1 Headcount FTE Mean_salary Median_salary
In post 2025 Female Actuary London London 50 45 88220 88750
In post 2025 Female Actuary Outside London Scotland 10 10 [c] [c]
In post 2025 Female Clinical London London 245 225 73340 60990
In post 2025 Female Clinical Outside London East (England) 105 95 53930 44960
In post 2025 Female Clinical Outside London East Midlands (England) 160 145 51180 44960
In post 2025 Female Clinical Outside London North East (England) 20 20 [c] [c]
In post 2025 Female Clinical Outside London North West (England) 50 45 71400 56090
In post 2025 Female Clinical Outside London Northern Ireland 20 15 [c] [c]
In post 2025 Female Clinical Outside London Scotland 80 75 55280 47960
In post 2025 Female Clinical Outside London South East (England) 295 255 59930 45560
In post 2025 Female Clinical Outside London South West (England) 335 285 50090 42230
In post 2025 Female Clinical Outside London Wales 185 160 58800 50680
In post 2025 Female Clinical Outside London West Midlands (England) 125 110 56470 46150
In post 2025 Female Clinical Outside London Yorkshire and The Humber 145 130 55370 43200
In post 2025 Female Clinical Overseas Overseas 25 25 [c] [c]
In post 2025 Female Clinical Unknown Unknown [c] [c] [c] [c]
In post 2025 Female Commercial London London 770 745 60630 60500
In post 2025 Female Commercial Outside London East (England) 160 150 51500 46790
In post 2025 Female Commercial Outside London East Midlands (England) 90 90 47940 44080
In post 2025 Female Commercial Outside London North East (England) 90 85 49210 42170
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 2025-07-16

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.
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Two bodies did not report any professions information for their employees. These are as follows: Scottish Forestry and Forestry and Land Scotland.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).