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Calendar year 2023
Supply of skills for jobs in science and technology
Data guidance
Published
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 (opens in a new tab).
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.
For sources that are already published in detail elsewhere, the accompanying dashboard (opens in a new tab) 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
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).
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
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 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
Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.
Education information is based on an employee's highest qualification in the 2018-19 tax year as identified in LEO.
Subject is based on Sector Subject Area for the FE and Apprenticeship pathways and JACS classification for the HE pathway.
The STEM classification is based on the subject of the qualification.
A Levels and GCSEs are undertaken as a bundle of qualifications and are therefor not allocated to a STEM category or subject.
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
Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.
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
Employees are those aged 23-30 in the 2018-19 tax year included in the ASHE survey and linked to LEO.
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
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