Data Science Skills Gap: The rising tide of digital technology is rapidly defining the twenty-first century.
Our every transaction, online interaction and the connected product is producing more and more data. And this means we’re increasingly able to derive powerful insight into human behaviour, preferences, trends and forecasts.
Around the world, such changes are providing a great opportunity. By 2020 the value of big data to the UK economy will be some £241 billion, creating 157,000 new big data-led jobs.
But such developments are not without their challenges.
Companies now wrestle with volumes of data and information that have never been encountered before. And the growth of big data shows no sign of slowing.
For instance, the total supply of information stored digitally and accessible to web users is now a monumental 4.4 trillion gigabytes. Most of this has been produced in the last few years. By 2020, this will amount to a 20,000-fold increase in the volume of data produced by businesses since 2000.
Firms are embracing these changes. They’re becoming increasingly data-driven, using larger amounts of data in everyday operations and investing in technology, processes and people. By 2020, 82% of UK executives plan to invest in AI, 70% in automation and 57% in blockchain.
But integral to enabling such processes and technologies are Data Scientists. Seen as the futurologists of digital technology, they also have claim to the “sexiest job of the 21st century”.
Data Science Skills Gap: Data Science & Scientists
The discipline of data science synthesizes the realms of statistics, mathematics and computer science with those of business intelligence and strategy. Through the application of scientific methods and innovations like machine learning, artificial intelligence, and data visualisation, data science turns vast quantities of available data into information.
And this process has the capacity to unlock powerful insights that are used to support strategic decision-making processes, enabling companies to gain a competitive advantage, drive profits and improve customer retention. In turn, it influences all aspects of our lives, from work to the home.
Particularly in sectors like finance, insurance, professional services and IT (accounting for 59% of total demand), the power and value that can be derived from their work have put Data Scientists in high and increasing demand. In return, experienced data scientists can earn around £100,000 per year.
Data Science Skills Gap: Shortage of Supply
In the face of this rapidly rising demand for Data Scientists – driven by the broader growth in the digital technology sector – there is a major issue of supply in the industry.
There are simply not enough people with the required combination of scientific, computational and analytical skills (and specific technical skills in areas like programming, coding, big data, machine learning, and AI) to meet the growth of demand in the industry.
This makes Data Science roles particularly difficult to hire for, translating into real differences in recruiting processes. Data Science roles take on average 45 days to fill, 5 days above the broader average.
And together these trends have created a growing Data Science skills gap.
In Europe, this manifests in a need for some 346,000 Data Scientists by 2020. In the UK, it risks having one million unfilled jobs in the IT sector by 2020.
Company executives are all too aware of this problem. 75% of UK executives are experiencing challenges in digital recruitment. 78% point to a shortage in data skills as the main barrier for data progression, and only 12% (down 8% from last year) think graduates have enough digital skills.
And this Data Science skills gap threatens to choke off the positive technological change and economic growth being driven by the sector, acting as a barrier to the development of firms in the UK and internationally.
Data Science Skills Gap: Filling the gap
The challenge lies in closing the deficit. However, there is no formal training process to become a Data Scientist. And this makes this already complex and competitive career path all the more difficult.
Specialised Data Science degrees are now emerging in the US and UK. And as we’ve explored in detail in a previous blog post, there are numerous ways you can boost your skills and experience in your own time. This includes improving your technical data skills in coding, big data technologies, or mathematics and statistics, to seeking practical experience through freelance work, internships or online courses.
But there are other options too – for instance, the Data Science bootcamp. Bootcamps offer a powerful learning solution to the individual looking to enter or upskill in the data science profession. But more broadly, they also offer a way to fill the broader Data Science skills gap the sector is struggling against.
We’ve explored some of the best bootcamps around in the UK. Broadly speaking they range from £3,000 – £15,000 in price and offer an excellent way to accelerate learning in the data science space, supporting the development of individuals in terms of key technical skills and experience through hands-on training, independent learning and collaborative projects, working one-to-one with mentors to build professional projects based on real data, and offering opportunities for network with hiring companies and data science professionals.
Data Science Skills Gap: Cambridge Spark – model bootcamp
One of our favourite companies offering such bootcamps at the moment is Cambridge Spark.
Cambridge Spark is one of the leaders in personalised Data Science training. They offer a range of bespoke corporate courses, apprenticeship and graduate scheme solutions, as well as their intensive bootcamps.
The Cambridge Spark Applied Data Science Bootcamp has participants ranging from people changing careers to executives looking to upskill and network. Their bootcamps help to build employability, technical skills and experience within the Data Science space. They achieve it by working through personalised, adaptive and industry-relevant technical training, offering the valuable aspects of online learning combined with the enriching, community features of learning in-person. Specifically, these benefits can be seen across five broad dimensions.
First, the Cambridge Spark bootcamp provides total immersion into the Data Science world. The course combines modules, mini-projects, and industry experience to create the complete learning package. Each module has hands-on projects, and there are frequent socials with Data Science leaders and AI summits. At the end of the bootcamp, there is a six-week capstone project with project partners to offer real-world experience on an end-to-end project, with real-world data.
Second, participants will be learning from instructors that are industry experts. Instructors either hold PhDs from the world’s leading universities or work in-industry as CEOs or as Senior Management of Data Science teams (from companies such as Morgan Stanley). As such, all teaching is in accordance with current industry practices. This allows participants to learn, apply and enhance their abilities in using those tools and techniques employers expect to see evidenced upon application.
3. Skills & Experience:
Third, the Cambridge Spark bootcamp is a superb mechanism to evidence the right skills and experience to employers. Undertaking their bootcamp allows participants to build expertise in Data Science tools and techniques and to build their portfolio of projects. Indeed, Cambridge Spark provides real-world data for each module undertaken. This allows participants to practice the processes of cleaning, analysing and applying data science tools and techniques.
To support this process, Cambridge Spark has a proprietary AI-powered adaptive learning platform called K.A.T.E ®. This platform assesses its students code upon submission to provide instant feedback on the quality of their code. It then suggests learning resources to help improve any areas that require developing. This enables candidates to iteratively make improvements to their skills and create production-ready code. At the same time, K.A.T.E ®. can also adapt the level of exercise difficulty depending on participant performance on previous exercises. This helps to create a deep and personalised learning experience.
Fourth, the bootcamp offers excellent support mechanisms throughout the experience. Participants thrive through a mix of online and offline support; it enables them to constantly reinforce their skills and learning as they move onto more advanced topics. Participants not only have significant direct in-person support, but they’re part of an extensive online slack and social media community. This enables them to learn from one another and to share learning resources they find useful to aid their learning and development. As Cambridge Spark’s participants come from diverse backgrounds and seniority levels, the community can use this extensive community to get advice and access to exclusive job opportunities too.
Finally, they offer a superb opportunity for networking. Participants will work with other professionals looking to re-skill and high-calibre Data Science professionals looking to up-skill. They will also meet others already working in the Data Science space through networking events. Networking events will be attended by Data Science Leaders, Hiring Managers and Project partners. This way, the participants can enhance their prospects of getting hired at the end of the bootcamp. At the same time, they are introduced to professionals to learn from too.
Data Science Skills Gap: The solution?
Despite the high cost, Data Science bootcamps can offer a great deal to the individual.
Carefully curated bootcamps like that of Cambridge Spark can offer an immersive, continuous learning and development experience. And this enables participants to build the employability, technical skills and practical experience required by the Data Science space.
However, while individuals can derive great benefit from such bootcamps, when it comes to the broader Data Science skills gap, they are no panacea.
Part of the problem is the sheer depth and complexity of the Data Science discipline, and for most, this takes years of study and professional experience to bridge.
Although bootcamps offer some support in closing the broader gap, they have to be one measure amongst many.
If our effort is sincere, the scale of the challenge requires concerted and consistent investment, educational reform and innovative solutions.
And closing this gap is vital.
The digital technology revolution is rapidly defining the twenty-first century. It has the potential to not only to enhance corporate value, boost efficiency and increase innovation but to change the very way human-beings organise as a species.
A modern economy like the UK has begun to take advantage of such processes, but we must do more – doing so might mean we won’t just be riding the wave, but shaping it.