Skills demand for
early career space jobs


  • This is the first quantitative assessment of skills demand in the UK space sector.
  • We analysed 812 early career UK space sector job adverts using our previously developed competencies taxonomy to identify competencies in highest demand within the UK space sector.
  • The most sought after technical skill is software development (required by 49% of all jobs), particularly in C/C++ (22%) and Python (20%).
  • This suggests the space skills shortage is largely a tech skills shortage, and shows that programming skills must be a strategic priority for the sector’s skills strategy.
  • There is also a high demand for transferable skills including interpersonal (84%) and communication (76%) skills.
  • This further demonstrates the importance of these skills, and that the sector must ensure that they are taught and developed alongside technical ones.


The UK’s space sector is growing at a rate of more than 3% per annum, creating hundreds of new jobs each year 1a, and has set the goal that it should have a global market share of 10% by 2030 2.

However, UK space companies are facing a skills shortage. 68% predict that they will be hiring over the next 3 years, but already more than half of large organisations report being worried about having access to skilled workers, and nearly 40% of all organisations say staff recruitment is a major barrier to their growth 1c.

Though there is a lot of anecdotal evidence of skills shortages in particular areas 3, there is very little detailed data available for the sector on the relative demand for different skills. Understanding exactly which competencies the sector is lacking is vital in informing provision of training and approaches to recruitment.

To address this, we have developed a taxonomy of space sector skills 4 and used this to give the first quantitative assessment of skills demand in the sector.

Though the sector normally talks about ‘skills’ shortages, in the rest of this document we use the word ‘competencies’ instead so that we can talk about traits, knowledge, skills, and qualifications separately.


Dataset is a British space jobs board operated by UKSEDS, the UK’s national student space society, which focuses on apprenticeships, internships, graduate schemes, PhDs, postdoctoral fellowships, and other early careers opportunities. The cutoff criterion is that positions require no more than three years of experience. We analysed job adverts posted on between December 2015 and December 2019.

The initial dataset contained just under 1300 adverts. We cleaned this dataset by removing duplicate adverts, and excluding all adverts which were not for internships, graduate positions, or direct entry jobs. This left us with 812 adverts (referred to as the SCUK dataset). The characteristics of the datasets are given in the Appendix, and its limitations are discussed in the Limitations section.

Competencies taxonomy

We analysed the dataset using our previously developed competencies taxonomy and library of natural language examples of competency descriptions. An overview of the taxonomy is provided here for context. The full taxonomy and a more detailed explanation of its structure can be found on a separate page.

The taxonomy has a hierarchical structure with up to five levels:

  1. Competency type (trait, knowledge, technical skill, transferable skill, or qualification)
    1. Trait – features of a person’s character or personality, embodied by certain behaviours
    2. Knowledge – facts or information about a given topic
    3. Technical skill – a skill which is specific to a sector or job
    4. Transferable skill – a skill which can be applied in a similar way to most jobs
    5. Qualification – a formal recognition of certain knowledge or skills following an assessment process by a relevant body
  2. Thematic area (science & engineering, programming & computer science etc.)
  3. Competency
  4. Subcompetency (if necessary)
  5. Subcompetency (if necessary)

Qualifications were not included in this analysis, but will be a topic of future work.

Each item in the taxonomy has a specific code representing the hierarchical levels. For example, the code ‘’ represents the following:
3 - Technical skills
  2 - Programming & Computer Science
    1 - Process and analyse data
      1 - Geospatial data
        1 - GNSS data


A competency can be described in a job advert in a number of different ways. For example, the taxonomic entry of ‘communication skills’ might be described as ‘communication and presentation skills’ or ‘written and verbal communication’.

A screenshot of the tagging system. On the left is text from a job advert with certain words and phrases highlighted. On the right is a list of those words and which tag in the taxonomy they relate to.
A sample job advert with tags

We measured how often each specific competency was mentioned across the whole dataset, and additionally how many job adverts mentioned at least one competency in each category. In this way, we obtained a measure of the frequency with which particular competencies were mentioned.

Subcompetencies were grouped with their parent competency, so mentions of ‘Matlab’ ( and ‘Python’ ( were counted towards ‘Design, develop, and deploy software’ (3.2.3).

Accuracy of analysis

We assessed the accuracy of our analysis by manually checking an additional randomly selected 50 job adverts and identifying any tags that had been missed or added incorrectly by the tagging algorithm.

Across the 50 jobs there were 468 tags in 383 categories. We found that 5 (1.3%) of these categories were incorrect – for example an advert for an administrative role described the employer as an ‘electronics’ company, and the job was incorrectly classified as requiring knowledge of electronics. We also found that there were 30 tags (6.4%) that we would have applied but had not been by the algorithm – for example we would have tagged ‘autonomous and challenge-driven’ as an example of the skill of working independently.

These errors were not corrected, as we aimed to strike a balance between the time needed to manually classify all the jobs and the error rate associated with doing so automatically, and we believe that this low error is an acceptable tradeoff. We hope to improve this error rate in future work.

Job classification

We classified the jobs manually by specific functional area based on their job title using the keywords below and the text of the job description where necessary. We then grouped functional areas into the categories and subcategories shown below.

Jobs were only classified into one functional area. Jobs which spanned more than one area were classified into the most relevant area, but we recognise that this will not always be a perfect fit.

Job area categories and indicative keywords.
CategoryIndicative Keywords
General engineeringEngineer (where not otherwise categorised below)
Electrical & Electronic engineeringElectrical, electronics, RF, microwave, PCB, antenna, spectrum, avionics, communications
Systems & AITSystems engineer, design engineer, quality, robotics, instrumentation
Mechanical, Thermal, and PropulsionMechanical, thermal, insulation, propulsion, CAD, materials, launch systems
Mission operationsSpacecraft control, satellite operations, control systems, ground systems, mission operations & planning
Computing & Data Analysis 
Software engineeringSoftware, developer, UX, website, cyber
Data analysisData analyst, data scientist
Remote sensingRemote sensing, GIS, GNSS, Earth observation
Science researchScientist, researcher, astronomer
BusinessBusiness analyst, business manager, business development, bid manager, PR & communications, marketing, sales
AdministrationAdministrator, assistant, receptionist, events, finance, HR, IT, project manager
Education & OutreachTeacher, education & outreach officer, presenter, explainer,
PolicyPolicy, law, regulation, contracts

Employer classification

We classified business employers manually by size and by segment using the information provided on their websites and LinkedIn profiles. Non-business employers such as universities, non-profits, and outreach providers are not included in size breakdowns.

Size classifications

We used the OECD’s definitions for business size for our classification 5.

Employer business area category definitions.
Business SizeNumber of employees
Micro1 - 9
Small10 - 49
Medium50 - 249

Segments classifications

We used segment definitions that are broadly the same as those used by the UK Space Agency 1.

Employers were only classified into one business area. Employers whose activities spanned more than one business area were classified into the most relevant area, but we recognise that this will not always be a perfect fit.

Employer business area categories and associated segments.
Business AreaSegment
Satellite/payload manufacturingUpstream
Subsystem supplierUpstream
Component/materials supplierUpstream
Prime/system integratorUpstream
Testing Upstream
Launch vehicles and subsystemsUpstream
Launch servicesUpstream
Ground segment equipmentUpstream
Software, IT, and other engineering servicesVaried depending on company specialism
Ground segment operatorDownstream
Satellite operationsDownstream
Satellite service provision (broadcast, comms, navigation, EO, weather etc.)Downstream
Sat data processingDownstream
User equipmentDownstream
Satellite data userDownstream
Research & developmentAncillary
Policy & regulationAncillary
Finance, insurance, and other support servicesAncillary
Education & outreachAncillary


In this section we present the top competencies identified by our analysis of the SCUK dataset, with a cut-off of appearing in at least 10% of jobs. We identify the competency type, specific competency, and the percentage of jobs within the dataset which mention the competency or one of its subcompetencies. We present the top competencies by company size and segment, and by job classification.

The ‘all jobs’ figures presented below are not weighted to characteristics of the UK space sector, so in cases where there is significant variation in demand between different sector segments or sizes of employer, the ‘all jobs’ figure may not be an accurate representation of the sector as a whole and the segmented tables should be used instead (see the Limitations section).

Competency demand for all jobs

Percentage demand for top competencies (those appearing in at least 10% of jobs).

Competency demand by job area

Percentage demand for top competencies (those appearing in at least 10% of jobs) split by job area.
Competency All jobs Engineering Computing & Data Analysis Science research Business Administration Policy Education & Outreach Other
  n = 812 n = 339 n = 207 n = 44 n = 83 n = 65 n = 18 n = 32 n = 7
Interpersonal skills 84 81 82 89 89 91 72 91 71
Communication skills 76 76 65 82 93 85 89 88 86
Design, develop, and deploy software 49 49 86 43 11 15 11 9 0
Analytical skills 46 54 46 55 36 28 72 6 14
English 38 33 35 45 55 45 67 13 43
IT skills 33 24 44 9 31 65 44 34 29
Self-motivated 23 23 22 25 30 26 6 13 0
Resourceful / proactive 22 22 19 18 34 22 28 19 29
Work independently 21 18 19 16 28 26 39 28 0
Willing to travel 20 15 23 16 19 34 17 22 14
Enthusiastic 18 15 16 23 19 20 0 53 14
Flexible 18 15 15 16 17 34 28 25 14
Practical / hands on 17 27 13 18 6 8 6 13 0
Process and analyse data 17 15 33 18 2 8 6 0 0
Knowledge of electronics 17 32 9 2 2 9 0 0 0
Problem solve 16 21 16 7 13 17 6 3 0
Planning & organisation 16 12 8 25 27 26 28 34 29
Attention to detail 15 16 11 7 13 29 6 13 14

Competency demand by job subarea (Engineering)

Percentage demand for top competencies (those appearing in at least 10% of jobs) split by job Engineering subarea.
Competency All jobs Mechanical, Thermal, and Propulsion Electrical & Electronic engineering Systems & AIT Technician
  n = 812 n = 53 n = 133 n = 57 n = 12
Interpersonal skills 84 89 82 91 75
Communication skills 76 81 72 70 75
Design, develop, and deploy software 49 40 50 51 17
Analytical skills 46 74 51 54 8
English 38 36 32 16 25
IT skills 33 30 22 21 50
Self-motivated 23 28 17 26 8
Resourceful / proactive 22 25 22 25 17
Work independently 21 19 17 18 17
Willing to travel 20 17 15 21 0
Enthusiastic 18 15 14 12 8
Flexible 18 13 12 18 17
Practical / hands on 17 40 25 32 17
Process and analyse data 17 2 21 21 0
Knowledge of electronics 17 13 51 26 25
Problem solve 16 28 21 25 42
Planning & organisation 16 15 8 14 50
Attention to detail 15 17 19 16 50

Competency demand by job subarea (Computing & Data Analysis)

Percentage demand for top competencies (those appearing in at least 10% of jobs) split by job Computing & Data Analysis subarea.
Competency All jobs Software Engineering Data Analysis Remote sensing
  n = 812 n = 132 n = 21 n = 50
Interpersonal skills 84 84 86 76
Communication skills 76 66 62 64
Design, develop, and deploy software 49 95 71 70
Analytical skills 46 36 67 66
English 38 41 19 26
IT skills 33 53 14 36
Self-motivated 23 27 10 14
Resourceful / proactive 22 23 10 14
Work independently 21 19 14 22
Willing to travel 20 24 24 16
Enthusiastic 18 17 0 12
Flexible 18 15 5 18
Practical / hands on 17 10 14 14
Process and analyse data 17 23 33 62
Knowledge of electronics 17 11 5 0
Problem solve 16 17 0 18
Planning & organisation 16 8 10 8
Attention to detail 15 11 10 12

Competency demand by employer segment

Percentage demand for top competencies (those appearing in at least 10% of jobs) split by employer segment.
Competency All jobs upstream Downstream ancillary academia
  n = 812 n = 279 n = 184 n = 331 n = 18
Interpersonal skills 84 82 83 86 72
Communication skills 76 76 66 82 72
Design, develop, and deploy software 49 52 60 41 22
Analytical skills 46 48 49 43 33
English 38 37 34 41 17
IT skills 33 28 35 36 22
Self-motivated 23 24 17 25 22
Resourceful / proactive 22 28 14 20 33
Work independently 21 17 20 24 33
Willing to travel 20 16 22 20 39
Enthusiastic 18 15 13 23 17
Flexible 18 13 23 19 11
Practical / hands on 17 22 13 16 28
Process and analyse data 17 13 25 15 11
Knowledge of electronics 17 28 8 12 17
Problem solve 16 15 11 20 17
Planning & organisation 16 10 11 24 22
Attention to detail 15 16 10 16 11

Competency demand by business employer size

Percentage demand for top competencies (those appearing in at least 10% of jobs) split by employer size.
Competency All jobs micro small medium large
  n = 812 n = 35 n = 94 n = 207 n = 281
Interpersonal skills 84 86 82 90 79
Communication skills 76 54 71 67 83
Design, develop, and deploy software 49 54 49 48 61
Analytical skills 46 34 43 42 56
English 38 31 36 35 38
IT skills 33 23 44 37 32
Self-motivated 23 14 28 32 20
Resourceful / proactive 22 6 28 24 21
Work independently 21 9 24 21 16
Willing to travel 20 14 28 14 23
Enthusiastic 18 20 14 17 21
Flexible 18 17 27 17 15
Practical / hands on 17 20 31 17 16
Process and analyse data 17 17 18 15 21
Knowledge of electronics 17 23 20 28 13
Problem solve 16 17 19 14 17
Planning & organisation 16 14 20 14 12
Attention to detail 15 3 16 19 15

What does the data say?

Technical skills & knowledge

The most significant result in this analysis is the very high demand for software development and data analysis skills (49%), which are by far the most sought after technical skills. For comparison, the next highest technical competency is knowledge of electronics at just 17%.

Specifically, demand appears to be highest for expertise in C and C++ (22%), Python (20%), MATLAB (12%), and Java (11%). It should be noted that many adverts list multiple programming languages and state that experience with any is acceptable.

Unsurprisingly, this demand is highest in software engineering roles (95% vs 49% for all jobs), but these skills are in high demand across all segments and sizes of employers, and particularly in downstream companies (60%). This is significant because the downstream space sector – space applications and data companies – employs the vast majority (79%) of space sector workers and has grown at an average rate of 5% per annum in the last five years 1b, so the demand for these skills will only increase.

This aligns with the results of the EO4GEO Space/Geospatial Sector Skills Strategy which found “the results of the job advertisements analysis confirmed the importance of recognizing ‘Programming and development’ as a key EO/GI skill sets, alongside other skills sets such as ‘Analytical Methods’” 6.

Similarly, in remote sensing roles data analysis (62% vs 17% for all jobs) and GIS skills (71% vs 9%) are most in demand, CAD skills are wanted for mechanical, thermal, and propulsion engineering (52% vs 8%) and electronics skills are most in demand in electronic engineering roles (51% vs 19% for all jobs). These variations are also reflected in the analysis by company segment, with upstream companies demanding electronics and CAD skills, and downstream ones demanding data analysis and GIS skills.

Transferable skills

There is a very high demand for transferable skills ranging from ‘softer’ interpersonal and communication skills (84%), to ‘harder’ analytical and problem solving skills (46%). It is possible that true demand is higher still, as a requirement for certain transferable skills is often implied rather than specifically mentioned, though findings by the Skills Builder Partnership in analysis of job adverts across all sectors 7 suggest that this adverts for early career roles tend to be more explicit. A handful of job adverts make no mention of any transferable skills, focusing solely on technical ones.

Breaking down the demand for transferable skills by job area shows the unsurprising results that engineering roles require a practical or hands-on attitude (27% vs 17% for all jobs), and outreach roles require enthusiasm (53% vs 18%). Resourcefulness and proactivity are demanded more for business (34% vs 22%) and policy (28%) roles.

There is also a large degree of variation between job areas for analytical skills, ranking highest in mechanical, thermal, and propulsion engineering (74%), policy (72%), data analysis (67%), and remote sensing (66%), and lowest in outreach (6%), and technician roles (8%).

Adverts for technician roles ask for certain transferable skills such as attention to detail (50% vs 15% for all jobs) and organisation (50% vs 16%) much more often. This may accurately reflect higher demand for these skills in technician roles, but it may also be a result of distortions from a very small sample size of just 12.

The majority of transferable skills see very similar demand in both segments. A practical or hands-on attitude is in higher demand for upstream companies (22% vs 13% for downstream jobs) which is explained by the differences in typical job roles. Interestingly, upstream demand is also notably higher for people who are resourceful (28% vs 14%) and self-motivated (24% vs 17%), whilst downstream demand is higher for people who are flexible (23% vs 13% for upstream jobs). It’s not clear why these transferable skills show this variation, as at first glance they appear to be independent of the business area.


A large number of the most demanded competencies are traits. This is significant because these characteristics are more difficult to formally teach, and are typically cultivated over a long period from a very early age (such as creativity and self-motivation), or form part of a person’s personality or personal preferences (such as enthusiasm and willingness to travel). They are likely to be beyond the scope of the space sector’s immediate skills pipeline, but the sector should support efforts to develop character throughout formal and informal education.

What does this mean for the space sector?

An important point to note before examining the implications of these results on the space sector is that this data only tells us the demand for competencies and not where there are shortages. More work is needed before we can get a clearer picture of the sector’s skills shortages.

The space skills shortage is largely a tech skills shortage

The size of demand for programming skills over all other technical skills strongly suggests that the space skills shortage is largely a subset of the UK’s larger tech skills shortage, which has already been extensively documented. The House of Commons Science and Technology Committee said in 2016 that ‘the UK faces a digital skills crisis’ and found that the digital skills gap is affecting 93% of UK tech companies 8, and in 2018 the Edge Foundation reported that there were more than 600,000 tech vacancies 9.

Looking at the space sector specifically, the 2014 Space IGS Skills Theme Report highlighted a ‘lack of technical computing and programming skills in the workforce as a whole and recent graduates in particular’, drawing on data from NERC, AIRTO, and others 3a. The IGS report noted that:

In general […] employers did not have difficulty filling positions since the pool of applicants is global. Where indigenous graduates might lack the modelling and mathematical analysis skills these skills can be sourced from overseas.

Space Innovation and Growth Strategy 2014 ‐ 2030: Skills Theme Report 2

This is especially noteworthy in the context of Brexit, which is expected to significantly increase barriers to hiring from overseas and significantly impact the aerospace industry’s skills pipeline 10.

The very high demand for programming skills which we present has significant implications for the design of the space sector’s recruitment pipeline from school outreach through to ongoing professional development training. Programming skills must be a priority in the sector’s skills strategy.

Demand for these particular skills also puts the space sector in direct competition with the broader tech sector, which offers a higher profile (of the 20 most recognised brands in the world, 50% are tech companies 11) and higher average pay 12.

If it is to properly compete, then work must be done to address this imbalance and raise the profile of the space sector among tech professionals and graduates.

The root causes of the skills shortage must also be addressed. The tech sector has already invested a great deal of resources into tackling this problem. The space sector must draw on the lessons learned from this work in the development of its own strategy both independent of and in partnership with the tech sector.

Transferable skills are vitally important

It is perhaps unsurprising that our analysis shows a very high demand for transferable skills; it is to be expected from their very definition. However this is useful further evidence of the importance of these skills and the impact that not having them can have on a technically skilled candidate’s prospects.

The 2014 Space IGS Skills Theme Report highlighted a ‘lack of understanding of the importance of professional communication’ 3a, and research from the wider engineering and STEM sectors have reported that many employers feel graduates do not have these skills to the level that they expect. The 2016 Wakeham Review found that only 25% of employers felt that STEM graduates had the ‘work ready’ skills they needed 13, whilst the IET’s 2019 Skills Survey found that 73% of companies had a problem with candidates who have academic knowledge but lack workplace skills 14. This is considerably more than the 59% of companies that were concerned about a shortage of engineering or technical skills at a professional level.

These findings reinforce the importance of transferable skills, and the sector must ensure that they are taught and developed alongside technical ones.

Future work

There are a number of avenues for further research building on this analysis.

We intend to run similar analysis on other datasets that cover jobs outside of early careers to get an indication of if and how demand varies between different career levels.

We want to look more closely at demand for programming skills, particularly which languages are in most demand and why, and what work has already been done to attract people with these skills into the space sector and to upskill those already in the sector.

We also want to better understand how the demand we have identified compares to skills shortages within the sector. How many of the vacancies we have examined are being filled, and do those people who are recruited have all the skills that are being asked for?


Analysis limitations

Demand vs shortages

Our analysis gives an indication of the demand for certain competencies within the UK space sector, but without knowing the supply of workers with these competencies, we are not able to make conclusions about where the shortages are. This is an area for future research.

Adverts are a proxy

We assume that the competencies asked for in job adverts are the ones employers want, but this may not always be the case. Job adverts may be poorly written, or may treat certain skills (such as time management) as implicit and not necessary to specify.

Dataset limitations

Early careers bias

The SCUK dataset is made up of adverts for early career space jobs. The competencies demanded for early career jobs may be different from the demand across the sector more generally. In future work we will look at wider datasets to examine this in more detail.

Inclusion of non-UK jobs

Though we present our analysis as being an assessment of skills demand in the UK space sector, about 30% of the jobs in the SCUK dataset are based outside of the UK. Of these, most (28%) are based in Europe, primarily Germany (10%) and the Netherlands (4%). advertised these roles as they were open to British nationals, and we include them as many relate to work in which the UK is closely involved, or to agencies such as ESA of which the UK is a member country.

There is no indication that the demands of the European space sector are significantly different from those of the UK’s, and many of these roles may need to be duplicated in the UK after Brexit if the UK develops replacement for EU programmes such as Galileo 15.

UK regional bias

The SCUK dataset has a significant bias toward companies in the South East of England and Scotland at the expense of London, the South West, and the East of England compared to data from the UK Space Agency’s Size and Health report 1d.

Distribution of jobs in the SCUK dataset and employees in the Size and Health report by UK region.
RegionSCUK Dataset
(% of jobs)
S&H 2018
(% of employees)
North East0.22.2
North West1.65.6
Yorkshire and the Humber0.33.1
East Midlands5.22.1
West Midlands0.22.8
East of England5.710.5
South East53.921.6
South West9.43.2
Northern Ireland00.3
Other (includes jobs with no fixed location)5.20

It is not clear why this is the case, but as a result care should be taken when considering our findings in a regional context. We have chosen not to segment our results by region because the sample size for some regions is too small to be a useful indication of demand in those regions.

Upstream bias

The SCUK dataset is significantly biased toward upstream companies compared to data from the UK Space Agency’s Size and Health report 1b.

Distribution of jobs by segment in the SCUK dataset and the Size and Health report.
SegmentSCUK Dataset
% of jobs
S&H 2018
% of jobs

It is not clear why this is the case. One possibility is that upstream companies tend to be larger with well developed internship programmes and graduate intakes, while downstream companies tend to be smaller and less able to take on a large number of early career employees. Additionally, the Space Placements in Industry (SPIN) programme which places a large number of undergraduate and postgraduate students in primarily downstream summer internships is only represented in the SCUK data only as a single post per year and not as multiple individual posts.

As a result, where there is a significant variation between upstream and downstream demand for a competency (such as for data analysis skills), the ‘all jobs’ figure should not be considered an accurate picture of sector-wide demand, and instead demand should be looked at on a sector-specific basis.

Individual job bias cautioned that some schemes with large numbers of openings – for example the ESA Young Graduate Trainee Programme – are represented by only a single advert per year.


We are grateful to UKSEDS for sharing their data from, without which this work would not have been possible. We would also like to extend a special thank you to Portia Bowman and Rob Garner for their advice and ideas, to James Telfer and Jacob Smith for proofing this paper, to our advisors Ed Chester, Julia Hunter-Anderson, and Sheila Kanani, and to Nigel Bannister and Roy Haworth for their suggestions and support in developing the competency taxonomy.


This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You can copy, redistribute, and adapt what we’ve presented for any non-commercial purpose. However, you must give us credit and link back to this page. If you want to use it in a commercial context, get in touch with us at


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This appendix gives a breakdown of the characteristics of the SCUK dataset use in our analysis.

Breakdown by country

Distribution of jobs by country in the SCUK dataset.
Country Number of jobs (count) Number of jobs (%)
Austria 9 1.1
Belgium 9 1.1
Bulgaria 1 0.1
Canada 2 0.2
Chile 1 0.1
Czech Republic 2 0.2
Denmark 3 0.4
Europe Wide 2 0.2
Finland 7 0.9
France 20 2.5
French Guiana 2 0.2
Germany 79 9.7
Ireland 1 0.1
Italy 15 1.8
Japan 9 1.1
Luxembourg 7 0.9
Norway 1 0.1
Poland 2 0.2
Portugal 1 0.1
Spain 13 1.6
Sweden 4 0.5
Switzerland 2 0.2
The Netherlands 36 4.4
UK 573 70.6
USA 9 1.1
Worldwide 2 0.2

Breakdown by UK region

Distribution of jobs by UK region in the SCUK dataset.
Region Number of jobs (count) Number of jobs (%)
East Midlands 30 3.7
East of England 33 4.1
London 52 6.4
North East 1 0.1
North West 9 1.1
Scotland 50 6.2
South East 310 38.2
South West 54 6.7
Wales 3 0.4
West Midlands 1 0.1
Yorkshire and the Humber 2 0.2
Other 30 3.7
Non UK 237 29.2

Breakdown by job types

Distribution of jobs by type in the SCUK dataset.
Job Type Number of jobs (count) Number of jobs (%)
Apprenticeship 17 2.1
Direct Entry Job 410 50.5
Graduate Position 190 23.4
Internship 195 24.0

Breakdown by job category and functional area

Distribution of jobs by category and functional area in the SCUK dataset.
Category Functional Area Number of jobs (count) Number of jobs (%)
- Mixed 16 2.0
Administration Administration 14 1.7
Administration IT 6 0.7
Administration Events 7 0.9
Administration Finance 10 1.2
Administration HR 2 0.2
Administration Management 2 0.2
Administration Project management 21 2.6
Administration Recruitment 3 0.4
Business Business Analyst 7 0.9
Business Business Development 18 2.2
Business Communication 27 3.3
Business Marketing 17 2.1
Business Sales 14 1.7
Computing & Data Analysis Architecture 6 0.7
Computing & Data Analysis Artificial Intelligence and Machine Learning 3 0.4
Computing & Data Analysis Data Analysis 16 2.0
Computing & Data Analysis Data science 5 0.6
Computing & Data Analysis Geospatial 1 0.1
Computing & Data Analysis Software Engineering 124 15.3
Computing & Data Analysis Remote sensing 49 6.0
Computing & Data Analysis Web Development 3 0.4
Education & Outreach Outreach 32 3.9
Engineering Assembly, Integration and Test 12 1.5
Engineering Astrodynamics 16 2.0
Engineering Technician 12 1.5
Engineering Telecommunication 14 1.7
Engineering Control 12 1.5
Engineering Design 1 0.1
Engineering Electrical 11 1.4
Engineering Electronics 75 9.2
Engineering Systems & AIT 34 4.2
Engineering Materials 2 0.2
Engineering Mechanical 34 4.2
Engineering General engineering 33 4.1
Engineering Mission Planning 5 0.6
Engineering Propulsion 7 0.9
Engineering Quality 6 0.7
Engineering Systems 33 4.1
Engineering Space systems 5 0.6
Engineering Spacecraft Operator 18 2.2
Engineering Structural 3 0.4
Engineering Thermal 7 0.9
Other Education 3 0.4
Other Journalism 4 0.5
Policy Policy 18 2.2
Science research Science research 41 5.0
Science research Earth Science 2 0.2
Science research Physiology 1 0.1

Breakdown by employer segment and business area

Distribution of jobs by employer segment and business area in the SCUK dataset.
Segment Business Area Number of jobs (count) Number of jobs (%)
Ancillary Non-profit 26 3.2
Ancillary Policy and regulation 5 0.6
Ancillary Space agency 48 5.9
Ancillary Other 55 6.8
Ancillary Research & development 50 6.2
Ancillary Consultancy 8 1.0
Ancillary Academia 92 11.3
Ancillary Marketing and communications 3 0.4
Ancillary Education & Outreach 22 2.7
Ancillary Market research and consulting 3 0.4
Ancillary Recruitment 21 2.6
Downstream Downstream software and IT 1 0.1
Downstream Satellite data user 1 0.1
Downstream Ground segment equipment 5 0.6
Downstream Satellite meteorological service provision 3 0.4
Downstream Satellite operations 2 0.2
Downstream Sat data processing 47 5.8
Downstream Satellite communication service provision 24 3.0
Downstream Satellite EO service provision 30 3.7
Downstream Ground segment operator 22 2.7
Downstream Midstream software and IT 29 3.6
Downstream Midstream support services 27 3.3
Downstream Satellite navigation service provision 9 1.1
Upstream Upstream software and IT 1 0.1
Upstream Prime/system integrator 62 7.6
Upstream Launch services 7 0.9
Upstream Launch vehicles and subsystems 22 2.7
Upstream Component/materials supplier 36 4.4
Upstream Testing services 2 0.2
Upstream Upstream support services 4 0.5
Upstream Subsystem supplier 46 5.7
Upstream Robotics 4 0.5
Upstream Satellite/payload manufacturing 95 11.7

Breakdown by employer size

Distribution of business employers’ jobs by employer size in the SCUK dataset. Non-business employers (such as universities) are classified n/a.
Size Classification Number of jobs (count) Number of jobs (%)
Micro 35 4
Small 94 12
Medium 207 25
Large 281 35
n/a 195 24
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