09 May 2019
Data skills for all: discussion note
New research illustrates the increased demand for data science skills in the job market, and sets out mechanisms that can help build a stronger talent pipeline.
The Royal Society's report Dynamics of data science skills (PDF), led by Professor Andrew Blake FREng FRS, looks at the current demand for data professionals, and how this varies across industrial sectors and UK regions. It identifies four major areas for action to strengthen the UK’s data science talent base.
There is a high demand for people with data science skills, with specialists in the field being highly sought after across organisations, from government departments to technology start-ups. Demand for workers with specialist data skills like data scientists and data engineers has more than tripled over five years (+231%). Demand for all types of workers grew by 36% over the same period.
Two companion booklets have also been published. The case studies (PDF) highlight some personal stories of career paths in data science working across academia, industry, charities and government. The models and mechanisms (PDF) present innovative, existing approaches which could be implemented more widely to meet demand and share talent.
For the UK to meet the needs of employers and maintain its position as a leading data research nation, the report calls for action in four areas:
We're now exploring ways of taking each of these areas for action forward. Our first event, Data skills for all (pdf), was a workshop held in partnership with STEM Learning focussing on developing foundational skills.
From transport to banking to shopping, everyday activities are increasingly leaving digital footprints that are transforming the world of work. The pervasiveness of data is rewriting the rules of many professions, and employers are increasingly seeking workers who can help them make sense of it.
The report analyses the demand for professionals with highly specialist data expertise, which includes roles like data scientists, data engineers, statisticians, biostatisticians, economists and financial quantitative analysts.
To understand the scale of demand, the Royal Society commissioned labour market software analytics company Burning Glass Technologies to mine millions of job adverts posted on employer websites. The software collected all UK-based job ads posted on 7,500 online jobsites over a five-and-a-half-year period.
The algorithm then extracted information about each job vacancy to detect whether it required data expertise, which includes roles as varied as marketing managers, risk consultants and business analysts. The research separately analysed roles requiring more advanced data skills, like data scientists and statisticians.
Of the 9.2 million job adverts, just over one in ten (996,000) required data expertise, with 345,000 based in London. The report found growing demand for data expertise in every UK region.
The analysis also looked at the types of skills most frequently required by British employers. The research shows that data science, scripting languages, big data, SQL databases and machine learning are the most frequently needed skills by employers, and increasingly required for data specialists, compared to five years ago.
This project is centred around a vision in which the UK is a leading data science research nation with a sustainable flow of expertise, and dynamic interfaces between industry-academia-public sectors. To achieve this, diverse data science skills are integrated into curricula in order to develop future users, developers and citizens. As a profession, data science provides an exciting and fulfilling career choice and is applied to procure broad societal benefit. Lastly, data and appropriate infrastructure are available across sectors.
A step change for education
The findings provide more evidence that the nature of work is changing, particularly due to new technologies like machine learning and artificial intelligence. To ensure young people leave school with the best possible start, the report calls for curriculum change in schools within the next ten years. This should include the opportunity to study a wide range of subjects to 18, and to develop valuable transferable skills such as communication, problem solving, and teamwork – well suited for the interdisciplinary nature of data science.
The report also recommends change at universities to retain and create the trained staff to meet these teaching needs. Professional-level courses should be flexible and responsive. Training may need to be industry-approved and accredited, and coordination is needed between industry and universities. More informal mechanisms such as online material are also needed to allow people to (re)train through self-learning.
Data science particularly lends itself to movement of talent between sectors, including on shorter timescales. The ability to do this will be enhanced by recognising the value of cross-sectoral working and braided careers (reciprocal arrangements that enable an individual to pursue dual, or even multiple, employment opportunities). This requires each sector to broaden its criteria and incentives to recognise and welcome more diverse forms of experience, for example academics gaining experience in the public sector or in start-ups.
Funding bodies like UK Research and Innovation (UKRI) could support joint appointments for the UK’s most talented researchers to work in both industry and academia.
Access to underlying infrastructure
Availability of data and computing power are major draws for talent. Industry dominates, offering both at considerable scale. The public and university sectors can also become more attractive to talented workers by investing more in the particular computing equipment that data science needs.
Professor Andrew Blake FREng FRS, chair of the project Working Group, said:
“Capturing, interpreting and being informed by data can radically transform a business, so it is only natural that employers are catching on to the potential of hiring data experts. This report shows the British economy has high demand for people with data skills, particularly at the advanced end of the spectrum, where businesses are crying out for professionals to unlock the potential of new technologies like machine learning and artificial intelligence. Demand shows no sign of slowing down, and skill shortages that have plagued the economy for years will only get worse over time.
“More needs to be done at universities too, where the intense hiring drives of tech giants increasingly lead to an exodus of researchers seeking better data, more computing power and higher salaries. More joint university and industry positions could help ensure that talented scientists stay in academia and train future generations to come. Universities may want think about embracing this joint model for data science and AI, to help secure their AI talent for the future.”