Civil Service Statistics data browser (2024)

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

Status Year Region_london Sex Sexual_orientation Profession_of_post Headcount FTE Mean_salary Median_salary
In post 2024 London Female Heterosexual / straight Commercial 535 520 59110 58250
In post 2024 London Female Heterosexual / straight Communications 805 775 51620 47470
In post 2024 London Female Heterosexual / straight Corporate Finance 10 10 [c] [c]
In post 2024 London Female Heterosexual / straight Counter Fraud 670 625 37920 33990
In post 2024 London Female Heterosexual / straight Digital, Data and Technology 1335 1290 54580 50200
In post 2024 London Female Heterosexual / straight Economics 430 410 55510 57150
In post 2024 London Female Heterosexual / straight Finance 955 915 52100 47240
In post 2024 London Female Heterosexual / straight Geography [c] [c] [c] [c]
In post 2024 London Female Heterosexual / straight Human Resources 1695 1610 52400 47700
In post 2024 London Female Heterosexual / straight Inspector of Education and Training 65 65 69150 68920
In post 2024 London Female Heterosexual / straight Intelligence Analysis 355 335 41620 38680
In post 2024 London Female Heterosexual / straight Internal Audit 70 65 52890 52190
In post 2024 London Female Heterosexual / straight International Trade 300 295 54610 57860
In post 2024 London Female Heterosexual / straight Knowledge and Information Management 240 225 42310 39000
In post 2024 London Female Heterosexual / straight Legal 1960 1815 62570 61260
In post 2024 London Female Heterosexual / straight Medicine 180 170 67440 57150
In post 2024 London Female Heterosexual / straight Operational Delivery 14375 13300 37580 33980
In post 2024 London Female Heterosexual / straight Operational Research 135 125 56510 57150
In post 2024 London Female Heterosexual / straight Other 935 890 45810 39190
In post 2024 London Female Heterosexual / straight Planning 35 30 58680 57330
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 2024-07-25

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.
Four 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, Scottish Forestry and Forest and Land Scotland. A further three organisations also could not provide entrants data in 2021. These are as follows: Department for International Development, Foreign and Commonwealth Office (excl. agencies) and Royal Fleet Auxiliary.
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.
Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
Sexual_orientation Self reported sexual orientation.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their sexual orientation and "Unknown" accounts for employees who have not made an active declaration about their sexual orientation.
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).