| Status | Year | Function_of_post | Region_ITL3 | Region_ITL2 | Organisation | Headcount | FTE | Mean_salary | Median_salary |
|---|---|---|---|---|---|---|---|---|---|
| In post | 2025 | Analysis | Aberdeen City and Aberdeenshire | North Eastern Scotland | Department for Environment, Food and Rural Affairs (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Aberdeen City and Aberdeenshire | North Eastern Scotland | UK Statistics Authority | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Angus and Dundee City | Eastern Scotland | Department for Work and Pensions (excl. agencies) | 5 | 5 | [c] | [c] |
| In post | 2025 | Analysis | Ards and North Down | Northern Ireland | Companies House | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Ards and North Down | Northern Ireland | Food Standards Agency | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Ards and North Down | Northern Ireland | UK Health Security Agency | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Armagh City, Banbridge and Craigavon | Northern Ireland | Department for Environment, Food and Rural Affairs (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Armagh City, Banbridge and Craigavon | Northern Ireland | UK Health Security Agency | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Babergh and Mid Suffolk | Suffolk | Department for Environment, Food and Rural Affairs (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Babergh and Mid Suffolk | Suffolk | Food Standards Agency | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barking & Dagenham and Havering | Outer London - East and North East | Department for Work and Pensions (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barking & Dagenham and Havering | Outer London - East and North East | UK Statistics Authority | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barnet | Outer London - West and North West | Department for Work and Pensions (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barnet | Outer London - West and North West | UK Health Security Agency | 30 | 30 | 62760 | 59750 |
| In post | 2025 | Analysis | Barnet | Outer London - West and North West | UK Statistics Authority | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barnsley | South Yorkshire | Department for Work and Pensions (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Barnsley | South Yorkshire | Department of Health and Social Care (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Bath & North East Somerset and South Gloucestershire | West of England | Department of Health and Social Care (excl. agencies) | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Bath & North East Somerset and South Gloucestershire | West of England | Food Standards Agency | [c] | [c] | [c] | [c] |
| In post | 2025 | Analysis | Bath & North East Somerset and South Gloucestershire | West of England | Ministry of Defence (excl. agencies) | 80 | 75 | 45750 | 40650 |
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 2025-07-18
| 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). |
| Organisation | Executive Agencies, Ministerial and Non-Ministerial Departments, Crown Non-departmental Public Bodies. |
| Region_ITL2 | 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 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland. | |
| Region_ITL3 | 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 3 divides into counties, unitary authorities, or districts in England (some grouped), groups of unitary authorities in Wales, groups of council areas in Scotland, groups of districts in Northern Ireland. | |
| 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. | |
| 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). |