Calendar year 2023

Supply of skills for jobs in science and technology

Data guidance

Published 9 May 2024

Description

This page describes the underlying data files for the ‘Supply of skills for jobs in science and technology’ ad-hoc official statistics release. This data is released under the terms of the Open Government License.

The publication methodology explains the definitions used and how estimates have been produced. It also provides information on the data sources, their coverage and quality.

Coverage

The data provided mostly relate to the UK labour market. The exception to this is the Education Pathways data, which are for people in employment in England across the 2016-17 to 2018-19 tax years and who have education records in the National Pupil Database for England. 

Full details of the coverage for each source are provided in the publication methodology.

For sources that are already published in detail elsewhere, the accompanying dashboard may include more of the published information than is contained in this release.

File formats and conventions

The underlying data files are provided in comma separated value (csv) format.

Rounding and decimal places vary across the different files, based on conventions for the relevant sources and what is appropriate for the analysis that has been undertaken.

Data files

All data files associated with this releases are listed below with guidance on their content. To download any of these files, please visit our data catalogue.

UK STEM employment by industry

• Filename: uk_science_technology_employment_by_industry2.csv
• Geographic levels: National
• Time period: 2023
• Content:

  Employment data for occupation groups, based on ONS SOC (details of group definitions are available in the publication methodology), and industry groups defined by ONS based on SIC (see footnote):

  • Employment volumes presented in millions, to one decimal place. Data from Annual Population Survey July 2022 - June 2023, sourced from ONS NOMIS

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
employment	Employment (millions)
group	Occupation group - Filter by occupation
industry	Industry - Filter by industry

Footnotes

1.  STEM industries use the ONS industry classification as indicative figures but is not formally defined in this report (https://www.ons.gov.uk/businessindustryandtrade/business/activitysizeandlocation/adhocs/14189stemindustriesbysize).
2. Not STEM includes Medicine and Health.

UK STEM employment growth

• Filename: uk_employment_change_2013_to_2023.csv
• Geographic levels: National
• Time period: 2013 to 2023
• Content:

  Employment volume and growth for occupation groups. Data from Annual Population Survey July 2022 - June 2023 and July 2012 - June 2013, sourced from ONS NOMIS:

  • Employment volumes presented in millions, to one decimal place
  • Details of group definitions are available in the publication methodology

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
employment	Employment (millions)
group	Group of occupations - Filter by occupation group
growth_since_2013	Growth since 2013

Footnotes

1. Data for 2021 onwards is based on SOC 2020, and data prior to 2021 is based on SOC 2010.
2. Not STEM includes Medicine and Health.

UK STEM employment by occupation

• Filename: uk_science_technology_employment_stem.csv
• Geographic levels: National
• Time period: 2023
• Content:

  Employment data for each SOC Unit group (4 digit) from Annual Population Survey July 2022 - June 2023, sourced from ONS NOMIS:

  • Employment volumes, rounded to nearest 100
  • Female % of employment
  • Annual % growth from July 2021-June 2022 data

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
Employment	Employment
Employment_growth	Employment growth
Female_percent	Female percent
Occupation	Occupation - Filter by occupation

Footnotes

1. Not STEM includes Medicine and Health.

UK STEM employment projections scenarios

• Filename: uk_science_technology_future_projections_scenarios.csv
• Geographic levels: National
• Time period: 2013 to 2030
• Content:

  Unit for Future Skills employment projections of numbers of jobs for each year to 2030 in different scenarios, for groups of occupations. Based on the Skills Imperative 2035 Employment and Skills Projections.

  Provided for Baseline, High growth, Population growth, and Technological growth scenarios.

  Details of scenario and group definitions are available in the publication methodology.

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
employment_projection	Employment projection
group	Group of occupations - Filter by occupation group
scenario	Growth scenario - Filter by projection scenario

Footnotes

1. Data for 2021 onwards is based on SOC 2020, and data prior to 2021 is based on SOC 2010.
2. Not STEM includes Medicine and Health.
3. Projections from the Skills Imperative 2035 are rebased for employment data from the Annual Population Survey, July 2022-June 2023.

England science and technology education pathways

• Filename: england_science_technology_education_pathways.csv
• Geographic levels: National
• Time period: 2018-19
• Content:

  Details of education pathways prior to early career employment in England in different SOC2010 occupations (or groups of occupations), using pooled employment data from 2016-17, 2017-18, and 2018-19 tax years; where an employee appears more than once, we take the information from the latest tax year observed. Further details are available in the publication methodology.

  The 'proportion' measure shows the share of employees for a group defined by selecting filters from:

  • breakdown: filtering the group variable to show individual occupations or STEM sub-groups
  • group: to select a specific STEM sub-group or specific individual occupation
  • pathway: to select employees whose highest qualification was attained in Higher Education, Further Education, an Apprenticeship, or at A/AS Level or GCSE level
  • stem_qual: whether the highest qualification was in a STEM subject
  • top_10_subjects: whether the qualification is in a top 10 subject area for early career workers, and which one

  The 'all_occupations_proportion' measure is a comparator showing the share of employees for the group selected, but ignoring the occupation selection (defined by 'breakdown' and 'group').

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
all_occupations_proportion	Proportion across all occupations in England
breakdown	Type of breakdown - Filter by group or individual occupation
group	Group of occupations - Filter by group of occupation
pathway	Education pathway
proportion	Proportion within group of occupations
stem_qual	STEM qualification - Filter by STEM or Not STEM qualification pathway
top_10_subjects	Top 10 subject

Footnotes

1. Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.
2. Education information is based on an employee's highest qualification in the 2018-19 tax year as identified in LEO.
3. Subject is based on Sector Subject Area for the FE and Apprenticeship pathways and JACS classification for the HE pathway.
4.  The STEM classification is based on the subject of the qualification.
5. A Levels and GCSEs are undertaken as a bundle of qualifications and are therefor not allocated to a STEM category or subject.

England qualification levels for STEM employees

• Filename: england_qualification_levels_stem1.csv
• Geographic levels: National
• Time period: 2018-19
• Content:

  Data about highest qualifications prior to early career employment in England in STEM occupations, using pooled employment data from 2016-17, 2017-18, and 2018-19 tax years; where an employee appears more than once, we take the information from the latest tax year observed. Further details are available in the publication methodology.

  The 'stem_qualification' measure shows the share of people having a STEM-related qualification, within groups defined by level of highest qualification held and gender.

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
gender	Gender - Filter by gender
group	Group of occupations - Filter by occupation group
highest_qualification	Highest level of qualification - Filter by highest level of qualification
stem_qualification	Percent with a STEM qualification

Footnotes

1. Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.

England GCSE and A Levels held by STEM employees

• Filename: england_a_level_gcse_held_by_occupation.csv
• Geographic levels: National
• Time period: 2018-19
• Content:

  Data about the share of early career employees in England in different SOC2010 occupations (or groups of occupations), using pooled employment data from 2016-17, 2017-18, and 2018-19 tax years; where an employee appears more than once, we take the information from the latest tax year observed. Further details are available in the publication methodology.

  The 'employee_share' measure shows the share of employees for a group defined by selecting filters from:

  • group: to select a specific STEM sub-group
  • qualification_type: A Level or GCSE
  • subject: either Any A Level or specific A Level or GCSE subject

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
employee_share	Share of employment
group	Group of occupations - Filter by occupation group
qualification_type	Type of qualification - Filter by type of qualification
subject	Subject - Filter by subject

Footnotes

1. Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.
2. GCSE and A Level and information is based qualifications achieved up to the 2018-19 tax year as identified in LEO.

UK Skills Imperative 2035 employment projections by occupation

• Filename: uk_science_technology_future_projections_occ.csv
• Geographic levels: National
• Time period: 2021 to 2035
• Content:

  Skills Imperative 2035 Employment and Skills Projections of numbers of jobs for each year to 2035, provided for each SOC Unit Group (4 digit), based on the value for the relevant SOC Sub-major Group (2 digit).

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
jobs	Employment projection
occupation_name	Occupation name (SOC2020) - Filter by occupation name

Footnotes

1. Not STEM includes Medicine and Health.

UK Skills Imperative 2035 employment projections by occupation group

• Filename: uk_science_technology_future_projections_group.csv
• Geographic levels: National
• Time period: 2021 to 2035
• Content:

  Skills Imperative 2035 Employment and Skills Projections of numbers of jobs for each year to 2035, provided for groups of occupations (details of group definitions are available in the publication methodology).

Variable names and descriptions

Variable names and descriptions for this file are provided below:

Variable name	Variable description
group_name	Occupation group (SOC2020) - Filter by occupation group
jobs	Employment projection

Footnotes

1. Not STEM includes Medicine and Health.