Civil Service Statistics data browser (2026)

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

Status	Year	Ethnicity	Region_london	Function_of_post	Sex	Headcount	FTE	Mean_salary	Median_salary
In post	2026	Asian	London	Analysis	Female	410	400	52320	49390
In post	2026	Asian	London	Analysis	Male	410	405	52450	49330
In post	2026	Asian	London	Analysis	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Commercial	Female	145	145	56920	50090
In post	2026	Asian	London	Commercial	Male	130	130	61020	52520
In post	2026	Asian	London	Commercial	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Communications	Female	125	120	50660	47270
In post	2026	Asian	London	Communications	Male	50	50	49340	47510
In post	2026	Asian	London	Communications	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Counter Fraud	Female	420	370	38730	37020
In post	2026	Asian	London	Counter Fraud	Male	310	300	40470	37240
In post	2026	Asian	London	Counter Fraud	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Debt	Female	150	125	32130	31470
In post	2026	Asian	London	Debt	Male	80	75	36930	31470
In post	2026	Asian	London	Debt	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Digital and Data	Female	655	640	53870	50390
In post	2026	Asian	London	Digital and Data	Male	815	810	57370	53250
In post	2026	Asian	London	Digital and Data	Unknown	[c]	[c]	[c]	[c]
In post	2026	Asian	London	Finance	Female	275	270	51810	50010
In post	2026	Asian	London	Finance	Male	255	250	52990	49930
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".
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.
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).