Civil Service Statistics data browser (2026)

Data preview: All civil servants / Parent_department / Region_london / Function_of_post / Sex

Status Year Parent_department Region_london Function_of_post Sex Headcount FTE Mean_salary Median_salary
In post 2026 Attorney General’s Departments London Analysis Female [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London Analysis Male 5 5 [c] [c]
In post 2026 Attorney General’s Departments London Commercial Female 10 5 [c] [c]
In post 2026 Attorney General’s Departments London Commercial Male [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London Communications Female 30 30 [c] [c]
In post 2026 Attorney General’s Departments London Communications Male 20 20 [c] [c]
In post 2026 Attorney General’s Departments London Digital and Data Female 35 35 48200 45980
In post 2026 Attorney General’s Departments London Digital and Data Male 35 35 59860 59170
In post 2026 Attorney General’s Departments London Finance Female 35 35 47410 39890
In post 2026 Attorney General’s Departments London Finance Male 30 30 42920 37620
In post 2026 Attorney General’s Departments London Legal Female 3020 2795 59720 63190
In post 2026 Attorney General’s Departments London Legal Male 1360 1325 61650 67190
In post 2026 Attorney General’s Departments London No function Female [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London No function Male [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London People Female 90 85 46500 39890
In post 2026 Attorney General’s Departments London People Male 35 35 48920 39890
In post 2026 Attorney General’s Departments London Project Delivery Female 20 20 [c] [c]
In post 2026 Attorney General’s Departments London Project Delivery Male 20 20 [c] [c]
In post 2026 Attorney General’s Departments London Property Female [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London Property Male 10 10 [c] [c]
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 2026-07-16

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.
Year Year of data collection (as at 31 March).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
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.
Of the 21 bodies under the Scottish Government, 16 did not report any functions information for their employees.
The Serious Fraud Office have not reported any data for profession, function, ethnicity, disabilty and sexual orientation due to alignment concerns with these fields with external reporting criteria. The Serious Fraud Office is currently undertaking work to ensure a robust dataset is reported for the 2027 ACSES return.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
Figures on sex presented here are based on management information provided by departments, which records the ‘legal sex’ of civil servants. ‘Legal sex’ does not align with ‘sex’ as defined by The Equality Act 2010.
The Serious Fraud Office have not reported any data for profession, function, ethnicity, disabilty and sexual orientation due to alignment concerns with these fields with external reporting criteria. The Serious Fraud Office is currently undertaking work to ensure a robust dataset is reported for the 2027 ACSES return.
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).