Civil Service Statistics data browser (2026)

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

Status Year Sex Region_london Profession_of_post Ethnicity Headcount FTE Mean_salary Median_salary
In post 2026 Female London Actuary Asian 10 10 [c] [c]
In post 2026 Female London Actuary Black [c] [c] [c] [c]
In post 2026 Female London Actuary Mixed [c] [c] [c] [c]
In post 2026 Female London Actuary Other ethnicity [c] [c] [c] [c]
In post 2026 Female London Actuary Undeclared [c] [c] [c] [c]
In post 2026 Female London Actuary Unknown [c] [c] [c] [c]
In post 2026 Female London Actuary White 40 35 96970 96950
In post 2026 Female London Clinical Asian 50 40 93490 76120
In post 2026 Female London Clinical Black 10 10 [c] [c]
In post 2026 Female London Clinical Mixed 10 10 [c] [c]
In post 2026 Female London Clinical Other ethnicity 5 5 [c] [c]
In post 2026 Female London Clinical Undeclared 10 10 [c] [c]
In post 2026 Female London Clinical Unknown 25 20 [c] [c]
In post 2026 Female London Clinical White 160 145 85770 75710
In post 2026 Female London Commercial Asian 100 95 59630 51730
In post 2026 Female London Commercial Black 75 75 55440 50290
In post 2026 Female London Commercial Mixed 30 30 60680 63010
In post 2026 Female London Commercial Other ethnicity 10 10 [c] [c]
In post 2026 Female London Commercial Undeclared 30 30 [c] [c]
In post 2026 Female London Commercial Unknown 70 70 59130 51740
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).
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".
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Three bodies did not report any professions information for their employees. These are as follows: Scottish Forestry, Forestry and Land Scotland and Serious Fraud Office.
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.
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.
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).