Sector Skills Needs Assessment – Life sciences
Updated 4 August 2026
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1. Handling notes
The SNAs use occupations, as defined by Standard Occupation Classification (SOC) codes, to provide an indication of the skills needs for the sectors. These allow for a consistent approach and cross-sector comparison. However, they are an approximation and do not work for all types of employment, particularly in highly specialised and emerging roles. As such, we have expanded our methods by using the newly developed UK Standard Skills Classification to identify the skill areas relevant for priority occupations.
This is the first step for assessing the future demand for skills across key sectors in terms of both occupations and specific skills areas. All estimates of future employment and skills are highly uncertain and their inclusion here is not for making precise forecasts of employment levels. Rather, the aim is to provide information about the general nature of changing employment patterns and their implications for skill requirements. The projections should be regarded as indicative of general trends and orders of magnitude, given the assumptions set out in section 5 below.
The data and methodology used to create the Skills Needs Assessments are set out in the accompanying tables and technical annex published alongside this report.
2. Executive summary
According to analysis by Skills England and the Office for Life Science, employment demand is expected to grow rapidly, with priority occupations in the life sciences sector projected to increase by around 66,000 jobs (44%) between 2025 and 2035, one of the fastest growth rates among priority sectors. In addition, an estimated 52,000 workers are expected to leave these priority occupations over this period and will need to be replaced, bringing total demand to around 118,000 workers overall.
Most projected additional employment (83%) in life sciences priority occupations requires qualifications at level 4 and above, reflecting the sector’s highly specialised skill needs and its strong reliance on higher education routes. Core skill requirements are particularly high in digital literacy, numeracy, and learning and investigating, alongside specialist scientific and regulatory knowledge.
Most priority occupations overlap with other sectors (28 of 31), with especially strong overlap with digital and technologies, intensifying competition for experienced digital, data and engineering talent. As with other sectors, there is a large amount of uncertainty over how AI adoption may affect future skills and staffing needs, particularly for digitally intensive roles.
Current demand pressures are already high, with 73% of life sciences priority occupations in critical or elevated demand across the UK economy, indicating widespread and acute recruitment challenges.
AI adoption across life sciences is accelerating, particularly in research, diagnostics, clinical trials and manufacturing. AI is primarily being used to augment scientific judgement, automate specific tasks, and reconfigure roles rather than replace them. This is leading to growing demand for hybrid ‘science and data/AI’ roles, alongside skills in governance, regulatory compliance, and the responsible use of AI in highly regulated environments.
Historically, education pathways into life sciences priority occupations are dominated by higher education. The most important pathways are at level 6 and above, particularly in computing, supported by a smaller contribution from digital technology apprenticeships at levels 2 to 5.
Growth in training is concentrated in digital and computing pathways, which align closely with priority occupations and have seen strong increases in achievements. Between 2021 to 2022 and 2023 to 2024, Computing qualifications at level 6+ grew by around 40%, and digital technology apprenticeships (level 2/3) grew by around 49%.
By contrast, growth in traditional routes such as engineering, economics, and mathematical sciences was more modest (around 6–7%). While business and management courses have expanded strongly, they have a comparatively low rate of progression into life sciences priority occupations.
3. Workforce overview and demographics
Life sciences is a highly-skilled and growing sector. In 2023 to 2024, it was estimated life sciences employed 360,000 people across the UK.
The life sciences sector consists of two core industries: biopharmaceutical businesses, which develop and produce pharmaceutical products, and medical technology businesses, which develop and produce medical devices and software. There is an integral link between the Life Sciences sector and the NHS.
As outlined in the Life Sciences Sector Plan the government intends to launch a substantial expansion and improvement of commercial clinical trials, positioning the UK to strengthen its research capability and global competitiveness. Alongside this, renewed emphasis will be placed on advanced manufacturing, supported by the £520 million Life Sciences Innovative Manufacturing Fund, which aims to accelerate innovation and scale-up across the sector.
The government has also set out ambitions to develop a world-leading data ecosystem by integrating genomic, diagnostic and clinical data at population scale, enabling more effective research, personalised healthcare and system-wide efficiencies.
Research from the Futures Group points to five major trends shaping workforce demands in life sciences: global macro-economic shifts, an evolving financial landscape for innovation, changes in regulatory requirements, rapid advances in digital technology, and the growing importance of sustainable development.
The Futures Group’s report, Life Sciences 2035 found that research, investment and employment in the sector remains particularly strong in the ‘Golden Triangle’ of London, Oxford and Cambridge, but there are distinct life sciences clusters through the UK, including the North West.
For other demographics, the age profile differs to that of UK-wide employment. As shown in Figure 1, there are notably high proportions of the life sciences workforce in the age groups of 25 to 34, 35 to 44, and 45 to 54 relative to those for UK-wide employment. The largest age group in life sciences is 35 to 44 (29.1%), which is 7.1 percentage points higher the UK average (22.0%). As shown in Figure 2, the workforce in life sciences is 59.1% male, compared to 52.0% across the UK.
Demographic data for age and sex below is based on the Futures Group definition of life sciences, published by Cogent Skills. The Futures Group is a collaboration between government and sector experts. The definition uses Standard Industrial Classifications (SIC) used by the Futures Group (Table A4, p6). Note that the SIC definition does not include the entirety of the life sciences sector. This SIC definition also differs from the Office for Life Sciences’ chosen definition, which is used for the regional data in Figure 3.
The diagrams ‘Figure 1: Age distribution for the life sciences (LS) workforce compared to UK-wide employment in 2023’, ‘Figure 2: Sex distribution for the life sciences (LS) workforce compared to UK-wide employment in 2023’ and ‘Figure 3: Regional distribution for the life sciences workforce compared to UK-wide employment in 2023’ have been removed because they could not be made accessible. If you need this information email accessibility@dwp.gov.uk and include the name of the publication.
Regionally, as shown in Figure 3, companies registered in the South East had the highest share of employment at 23.6%, which is 9.6 percentage points higher than the UK average (14.0%). Note that the regional data shown in Figure 3 for life sciences is based on the location of a company’s registered address and may therefore differ from the actual workforce location.
Within the South East, based on bioscience and health technology sector statistics 2023 to 2024, employment in life sciences companies is concentrated across a number of local authority areas. The highest levels are seen in Wokingham (7,761), Basingstoke and Deane (7,162), Reading (6,977), and Buckinghamshire (6,709), highlighting a strong cluster along the Thames Valley.
Beyond the South East, there are also significant life sciences employment clusters across other regions, alongside a particularly strong hub in the East of England. In the East of England, employment is highly concentrated in Cambridge (13,061) and South Cambridgeshire (9,658), with additional activity in areas such as Dacorum (3,575), highlighting the importance of this region as a key centre of life sciences employment outside the South East and London.
Other regions also show notable concentrations. In Yorkshire and the Humber, employment is spread across Leeds (5,296), North Yorkshire (3,912), Kingston upon Hull (3,879), and Sheffield (3,373). In the North West, key centres include Warrington (4,674), Manchester (4,345), and Trafford (3,983), while in the West Midlands, employment is concentrated in Warwick (4,457) and Birmingham (3,287), demonstrating the presence of established sub-regional hubs.
Note: These figures are based on employment at life sciences companies by Local Authority District (UK, 2022 to 2023), and reflect the location of company registered addresses, which may differ from the distribution of the workforce in practice.
4. Priority occupations and current demand
4.1 Priority occupations
Skills England has been working with the Office for Life Sciences (OLS) to identify occupations of importance to their sector.
The method used by the OLS to identify priority occupations involved taking the SOC breakdown within each SIC code from ONS census data and applying this to a 3-digit SIC cut of OLS BaHTSS data. This produced a long list of SOC codes ranked by life sciences employment. The OLS worked together with industry stakeholders to then select the top occupations from this ranking which are relevant to the life sciences sector.
There are 31 priority occupations for life sciences, 28 of which overlap with at least one other sector. There are 9 priority occupations which overlap with more than one sector, including:
- programmers and software development professionals (overlaps with 7 sectors)
- IT business analysts, architects and systems designers (5)
- engineering professionals not elsewhere classified (n.e.c.) (5)
In terms of priority occupations, life sciences overlaps the most with digital and technologies, which shares 14 priority occupations.
There are 3 life sciences priority occupations which do not overlap with the priority occupations selected for any other priority sectors:
- chief executives and senior officials
- biological scientists
- natural and social science professionals n.e.c.
Table 1: Life sciences priority occupations appearing in at least 2 other sectors
| Occupation | Number of sectors including life sciences |
|---|---|
| Programmers and software development professionals | 7 |
| IT business analysts, architects and systems designers | 6 |
| Engineering professionals n.e.c. | 5 |
| Financial managers and directors | 4 |
| IT managers | 4 |
| Production managers and directors in manufacturing | 3 |
| Marketing, sales and advertising directors | 3 |
| Information technology directors | 3 |
| Quality assurance technicians | 3 |
Of the priority occupations in life sciences, 35% are in critical demand (substantially higher demand than usual) and 73% are in either critical or elevated demand (above average). This is based on Skills England’s Occupations in demand analysis, published in 2025, and illustrates a high level of current demand for the priority occupations identified by the sector.
4.2 Demand for skills
The UK’s first Standard Skills Classification (SSC) provides a mapping of relevant skill areas to occupations. Using an initial prototype of the SSC, experimental analysis was conducted to identify the skill areas which are relevant to priority occupations.
Across the 18 priority occupations with direct relevance to the life sciences sector (excluding the priority occupations which are supporting roles for the sector), the top 3 technical skill areas are:
- developing and deploying applications
- leading organisational operations and improvements
- analysing and interpreting information and data
Core Skills
The SSC also sets out 13 ‘Core Skills’, which are fundamental abilities that contribute to the capability to carry out the tasks associated with a specific job, such as numeracy, reading, and writing. They are often transferable, meaning they can be applied across different sectors of activity and roles. The SSC provides proficiency scores for core skills by occupation, on a 1 to 5 scale from minimal proficiency to expert proficiency.
The 13 Core Skills defined in the UK Standard Skills Classification (SSC) are listed below. These are foundational, transferable abilities required across occupations, and they are listed explicitly in the SSC Core Skills Explorer.
- planning and organising – setting goals, prioritising tasks, structuring approaches
- adapting – adjusting strategies or behaviour to new or changing situations
- working with others – collaborating effectively with teams or groups
- listening – understanding spoken communication, including non-verbal cues
- speaking – communicating clearly and confidently through speech
- leadership – motivating, guiding, and inspiring others
- learning and investigating – searching for, gathering, and understanding new information
- creating – developing original ideas, innovations, or solutions
- problem-solving and decision-making – identifying issues, analysing information, selecting solutions
- numeracy – applying mathematical techniques and interpreting numerical data
- digital literacy – using digital tools and technologies effectively (including AI)
- reading – interpreting written information accurately
- writing – communicating ideas clearly and persuasively in written form
The required proficiency in core skills for the priority occupations have been compared to the UK average. Where core skills have a higher required proficiency in priority occupations, this suggests that these skills are particularly important for these occupations. The graph below shows which core skills are important for the life sciences sector compared to the wider UK.
Across all life sciences priority occupations (including direct and supporting occupations), life sciences requires notably higher proficiency in the core skills:
- digital literacy (3.9 versus 3.2)
- numeracy (3.7 versus 3.1)
- learning and investigating (3.8 versus 3.2)
The diagram ‘Figure 4: Core skills proficiency for the life sciences sector compared to the UK’ has been removed because it could not be made accessible. If you need this information email accessibility@dwp.gov.uk and include the name of the publication.
5. Future demand for priority occupations
Within the life sciences sector, employment demand for priority sectors is projected to grow by 66,000 (44%) between 2025 and 2035.
Projected employment demand has been estimated using OLS Bioscience and Health Technology Sector Statistics (BaHTSS) and ONS census data. Total sector employment up to 2035 was estimated using BaHTSS data, applying the most recent 5-year historic growth rate to current employment levels.
Current occupation-level estimates were calculated by applying each industry’s occupation shares from census data to industry-level life sciences employment totals and aggregating across industries. Occupation-level estimates were scaled up so that their sum is equal to the total life sciences total employment value in each year of projections.
5.1 Top occupations by employment growth to 2035
As seen in Figure 5, the occupation with the highest projected employment demand is Programmers and software development professionals, with 6,300 additional workers needed in life sciences between 2025 and 2035. This occupation also faces demand from other priority sectors. The total projected employment demand for Programmers and software development professionals across all priority sectors, including life sciences, is 192,200 workers.
The priority occupation with the second highest projected employment demand is Production managers and directors in manufacturing, with 6,100 additional workers needed in life sciences between 2025 and 2035. The next highest occupations are Laboratory technicians and Research and development (R&D) managers, with 4,500 and 3,300 additional workers needed respectively.
Additional demand figures for all life sciences priority occupations can be found in the accompanying tables.
The diagram ‘Figure 5: Top 10 priority occupations in the life sciences sector by additional employment to 2035’ has been removed because it could not be made accessible. If you need this information email accessibility@dwp.gov.uk and include the name of the publication.
5.2 Expected qualification levels
The majority (83%) of projected additional employment in priority occupations requires workers with qualifications at level 4 and above. As shown in Table 2, this is far higher than across all priority occupations for the 10 priority sectors, where 62% of projected additional employment in priority occupations required workers qualified at level 4 and above.
Table 2: Expected qualification level of workers needed to meet demand to 2035 in priority occupations
| Priority Occupations | Level 2 or 3 | Level 4 or above |
|---|---|---|
| Life sciences priority occupations | 17% | 83% |
| All priority occupations | 38% | 62% |
Source: Skills England planning scenarios based on sector-level projections
5.3 Alternative scenarios
Any future projection of how the economy will evolve is inherently uncertain. This uncertainty increases the further forward the projection extends. To improve the understanding of the uncertainty in the skills assessment projections, Skills England asked the sponsoring department to provide an alternative scenario.
The total employment growth in the alternative scenario is shown in Table 3 below. Outputs in this alternative scenario have been calculated by applying economy-wide labour market projections from Skills Imperative to the 2025 employment estimates derived in the baseline approach. For occupational-level estimates, the Skills Imperative growth rates were applied to each occupation’s 2025 estimate. Then, as in the baseline scenario, these occupation-level estimates were scaled up so that for each year of projections, the sum of employment for all occupations equals the sector total.
In the alternative scenario, growth in priority occupations is lower by 48,000 workers (18,400) compared to the central scenario (66,400). The growth rate in the alternative scenario is 13%, which is 31 percentage points lower than the central scenario (44%).
Table 3: Alternative demand scenarios for life sciences
| Scenario | Increase in employment demand from 2025 to 2035 | Percentage change in employment demand from 2025 to 2035 |
|---|---|---|
| Central | 66,400 | 44% |
| Alternative | 18,400 | 13% |
Numbers rounded to nearest 100
Source: Life sciences demand projections provided by the Office for Life Sciences
The uncertainty in many of the projections is far greater currently due to the accelerated adopting of AI technology. Such technology will increase the productivity of many jobs and possibly reduce the demand for new workers in affected occupations. The speed of such changes will be uneven across the economy and very uncertain.
The uncertainty caused by AI has been a particular issue for the assessment of the life sciences sector, not least as digital occupations have seen some of the highest projected growth rates and these occupations are seeing some of the greatest AI-related changes. For the purposes of this assessment, we have not adjusted the projections provided by sector experts to take account of AI adoption as the evidence for changes is not currently strong. Furthermore, the growth in digital occupations is as much to do with the broad digitalisation of many sectors which is well established, as opposed to just a narrow growth in demand. However, it needs to be recognised that there is a heightened risk that projections of AI-exposed occupations including digital occupations are too high. Skills England intends to conduct some further work over the next year to understand the risks more fully.
5.4 Replacement demand
In addition to expansion demand, where we consider the additional workers needed due to expected future sector growth, there is also demand for workers required to replace existing workers in the labour market. This is known as replacement demand. This is a broad estimate, based on applying rates from The Skills Imperative economy-wide labour market projections.
Our analysis focusses on expansion demand and assumes currently supply is sufficient to maintain the existing size of the workforce. In practice, this will not be the case for some occupations. Each year we estimate an average of 5,200 workers needing to be replaced within priority occupations in life sciences. Over the 10-year period of 2026 to 2035, the total estimated replacement demand is 52,000 workers.
This increases the total demand for workers. When combining this with total additional employment demand to 2035 (66,400), the total demand for workers in life sciences is around 118,000 overall.
6. Influence of AI on the life sciences sector
AI is increasingly used in R&D and manufacturing, advancing discovery, genomic analysis and evidence synthesis; automating imaging and lab workflows; and tightening quality control and batch release in medicines manufacturing (AI skills for the UK workforce - GOV.UK, 2025; Genomic AI NHS Network, 2024; Genomics England, 2025; and deep-dive workshops with sector leads, 2026).
Adoption is uneven across firm size, which has direct implications for skills, governance, and training provision.
AI is reshaping work across life sciences in ways that blend augmentation, reconfigured tasks and selective automation. Rather than replacing scientific judgement, AI is increasingly used to extend it. These technologies are increasingly being used to automate genomic analysis, enhance diagnostic precision, and simplify production processes within pharmaceutical and biotechnology sectors.
Evidence collated as part of our sectors deep dives as part of fellowship work shows:
- augmentation - scientists use AI to scope literature, triage evidence and surface regulatory changes, while humans retain interpretation and sign-off
- task reconfiguration - hybrid ‘science + data/AI’ roles expand (for example bioinformatician–bench scientist, data/knowledge stewards)
- targeted automation - AI-enabled imaging, lab robotics and computer vision support sample prep, QC and root-cause analysis
The skills demand is not limited to technical AI roles in the sector. It reaches labs, clinical operations, manufacturing and commercial, intensified by government policy and market investment. The Life Sciences Sector Plan (July 2025) sets out a government–industry programme to speed clinical research and adoption, with delivery owners and performance/accountability metrics, signalling sustained demand for AI, data and translational skills across the product lifecycle.
Skills England has commissioned Dr Nisreen Ameen to develop an AI Skills tools package. As part of this, evidence from deep-dive workshops with sector leads and Skills England’s research and analysis report on AI skills for the UK workforce shows that AI skills in demand can be mapped to three broad domains:
Technical skills
- utilising AI for data analysis, automation, and predictive modelling in research
- applying data engineering principles
- operating and troubleshooting AI-enabled lab equipment and robotics
- embedding and developing AI in clinical trials, biobanks, and manufacturing
- leveraging low/no code tools
Non-technical skills
- communicating AI outputs, leading adoption projects, innovating and solving problems, mentoring others to use AI
- adaptability and curiosity with evolving AI tools
Responsible and ethical skills
- applying ethical and legal frameworks for patient data, intellectual property and regulatory compliance
- implementing governance and audit processes
- identifying and mitigating bias
- safe handling of sensitive biomedicine data
- assessing AI in regulated settings
7. Education supply
As part of this assessment, we have considered the supply of workers in priority occupations relevant to the life sciences sector. Employment in the sector is influenced by a range of joiners (inflows) and leavers (outflows), as illustrated in Figure 6. This analysis focuses on one component of supply: inflows from education.
Education inflows capture individuals who move from education into employment in priority occupations. This group is predominantly made up of career starters, while also including a smaller number of job switchers and individuals returning to work. Taken together, these flows provide a robust and consistent indicator of the pipeline of new talent entering priority occupations and form a reliable basis for understanding the contribution of the education system to workforce supply.
Figure 6 is a stock and flow diagram showing how people join the life sciences sector, listed as career starters, job switchers, returners, immigrants. It then shows what makes them leave: retirements, job switchers, labour market leavers, emigrants. For joiners, the diagram states that Skills England’s estimate of education leavers is predominantly career starters but will include some job switchers and labour market returners. For leavers, the diagram outlines that Skills England’s estimate of replacement demand includes retirement and semi-permanent labour market leavers (for example, due to illness, family formation).
7.1 Important training routes
There are multiple routes by which people enter employment in a given occupation. Using information on historic pathways into these occupations and the Skills England Occupational Maps, we have identified the most prominent routes that provide direct supply into priority occupations identified for the life sciences sector. These routes relate to entry into the occupation but cover all industries and are not specific to employment in the life sciences sector. These routes are summarised in Table 4.
Training routes are listed below by the proportion of education leavers in employment that enter a priority occupation listed by DCMS. The volume of education leavers is also listed for a particular route.
Key training routes broadly split into 3 types of courses:
- well-aligned routes, often technical in nature, where a high proportion of leavers progress into priority occupations, but sometimes with small cohorts
- balanced routes, where a reasonable proportion of leavers progress into priority occupations from a larger cohort
- high-volume routes, where a smaller proportion of leavers progress to priority occupations but contribute a large share of employment
Not all 3 course types are present in all sectors. For well-aligned routes, increasing the supply into priority occupations will likely require an increase in enrolments. Whereas for other routes that are less well-aligned, increasing the progression rates to priority occupations may be more effective.
Table 4: Key routes related to priority occupations for the life sciences sector
| Pathway | Subject area | Level group | Number of education leavers entering priority occupations | Percentage of employed education leavers entering priority occupations |
|---|---|---|---|---|
| Higher education | Computing | Level 6+ | 6,960 | 56% |
| Apprenticeship | Digital technology (practitioners) | Level 4/5 | 890 | 51% |
| Apprenticeship | Digital technology (practitioners) | Level 6+ | 520 | 51% |
| Higher education | Chemistry | Level 6+ | 940 | 44% |
| Higher education | Economics | Level 6+ | 1,920 | 39% |
| Higher education | Mathematical sciences | Level 6+ | 1,570 | 38% |
| Apprenticeship | Digital technology (practitioners) | Level 2/3 | 1,430 | 36% |
| Higher education | Engineering | Level 6+ | 4,520 | 34% |
| Higher education | Business and management | Level 6+ | 10,440 | 28% |
Source: Skills England estimates based on employment in 2022 to 2023 tax year
Note: The routes relate to entry into the priority occupations identified by the Office for Life Sciences but, as these occupations can span multiple sectors beyond Life Sciences, this analysis is not strictly specific to employment in the life sciences sector.
The 9 routes in Table 4 account for 45% of education leavers entering priority occupations for the sector. These important routes cover a range of subjects, reflecting the varied skills needs of the sector. The digital skills needs for the sector result in computing and digital subjects having the highest rates of education leavers entering priority occupations. This includes apprenticeships, though at a lower rate than computing higher education at level 6+.
Some newer training routes are not included in the historic data, including newer apprenticeship standards and Skills Bootcamps. Overall, based on the Skills England Occupational Maps, there are 99 apprenticeship standards linked to priority occupations in the sector. In the 2024 to 2025 data, the highest volumes were for business management apprenticeships and digital technology apprenticeships used across all sectors. Beyond these, engineering manufacturing technicians and laboratory technicians had among the highest achievements.
7.2 Trends in training routes
We can get a sense of how supply into priority occupations is changing by looking at the number of learners successfully completing a course (defined as ‘achievements’) that is aligned with these occupations. Where courses have grown in achievement numbers, this could suggest that these courses will continue to be key pathways into priority occupations in the sector. Table 5 gives an overview of the change in achievement figures for the key routes over the 2 years between 2021 to 2022 and 2023 to 2024.
Table 5: Growth in achievements for key routes related to priority occupations
| Pathway | Subject area | Level group | Achievements in 2023 to 2024 | Growth in achievements since 2021 to 2022 |
|---|---|---|---|---|
| Apprenticeship | Digital technology (practitioners) | Level 4/5 | 4,190 | +82% |
| Apprenticeship | Digital technology (practitioners) | Level 2/3 | 6,960 | +49% |
| Apprenticeship | Digital technology (practitioners) | Level 6+ | 1,840 | +46% |
| Higher Education | Business and management | Level 6+ | 187,750 | +41% |
| Higher Education | Computing | Level 6+ | 50,280 | +40% |
| Higher Education | Engineering | Level 6+ | 43,080 | +7% |
| Higher Education | Mathematical sciences | Level 6+ | 13,500 | +7% |
| Higher Education | Economics | Level 6+ | 17,710 | +6% |
| Higher Education | Chemistry | Level 6+ | 5,540 | +3% |
Source: Figures provided by the Department for Education
There is a considerable amount of growth in the computing and digital routes for this sector. These training routes have a high rate of entrants into priority occupations and are growing. For other areas of level 6+ higher education, the growth rate is steady. Business and Management at level 6+ higher education has seen a substantial level of growth. Though the rate of entrants into priority occupations for life sciences is relatively low compared with other training routes, the volume of entrants remains high. As such, this growth is unlikely to result in a large influx of entrants into the sector.