How can we close the data skills gap?
53% of senior executives have identified data and analytics as their top investment priority in the next two years. Are you one of them?
There’s a data skills gap in the UK, and it’s holding back the tech sector. According to Jigsaw Academy, only 20% of data scientists in UK have the right skills. In the key field of Big Data analysis, 22% have 'partial skills’.
What goes wrong when we can’t find the right data skills?
This year, we expect there will be a particular focus on operationalising data systems and scaling through increased connectivity. However, a lack of skilled data professionals could prevent 65% of businesses from fully utilising their data, cloud, and automation investments.
As a consultative tech recruitment agency, it's in our interest to help our clients close the skills gap in their organisations. One area that has seen a significant shortage in recent years is data; data science in particular.
Why is there a data skills gap?
Data science, data analysis, data engineering... 10 years ago these roles were virtually unheard of. Today, data skills are some of the most sought after in tech.
Businesses are waking up to the benefits of intelligent data strategies involving analysis, modelling, and productisation; and to realise this value, they’re searching for trained Data professionals.
Data science is an interdisciplinary field that uses scientific methods to extract knowledge from data. Data scientists have strong technical skills, but they also have excellent analytical instincts and can apply problem-solving skills on a large scale.
But hard skills, such as knowledge of big data storage, big data analytics, visualisation, and machine learning, are only part of the story.
What soft skills do data professionals need?
Good data professionals have an understanding of the business side of data, as well as the technology and practical elements.
Critical thinking skills, analysis, resilience and adaptability, leadership and social influence, reasoning and problem solving, and initiative taking are all soft skills the current tech landscape demands.
What type of data skills are in demand?
Data modellers and analysts are, compared to other skillsets, relatively easy to find. Derived from a systems analyst skillset, data modellers design databases; translating complicated business data into usable computer systems. They’re familiar with both conceptual and logical data modelling.
The skill deficit is most apparent when trying to find good quality data scientists. Data scientists need to have a solid understanding of data modelling, and more crucially – software engineering.
Data scientists need to query and connect to databases, implement object storage, develop containerised models, convert them into APIs, and develop edge devices.
In an enterprise context; the data scientist (or engineer) is the person you rely on to turn your output into a product capable of real-world use.
So, how can employers close the data skills gap?
In the emerging Big Data landscape, you don't want to be left behind. Research conducted by Virgin Media O2 estimated a total cost of £12.8 billion annually due to the digital skills shortage. 55% of organisations were found to be facing skill shortages.
Hire graduates with data skills
We have seen a real reluctance from tech employers to hire graduate and entry-level staff over the past few years. This cultural shift has created a detrimental entry-level skills deficit, and raised the bar for entry into tech.
"What’s becoming clear to me is if we don’t invest in entry-level cohorts, existing talent will upskill or age out of the industry. Skilled employees will become more expensive and harder to source. "
You could look into hiring data apprentices, too.
The BCS offers data-driven apprenticeships at a variety of levels. Apprentices work as they learn, meaning they are used to applying their theoretical knowledge in real-life scenarios. Many progress into senior a role quickly following the completion of their course.
Up-skill internal teams with training
Do you already have a data team? The demands of a data-driven tech landscape are continuing to shift and change. Research from EY indicates that organisations are still having trouble filling data-centric roles due to ineffective upskilling programmes, a shortage of talent, and more.
To get the most out of your investment, ensure you're providing additional training, exposure to peers, and access to learning/networking opportunities. Focusing on enterprise-level skillsets – like productising your output and developing future-proof systems – will ensure your data team creates positive ROI.
The more up-to-date your staff are on technologies and techniques, the better equipped you'll be to make sound business decisions. Plus, investment in employees’ professional skillsets is linked with a higher level of satisfaction, so – it's a win/win situation.
Work with education providers to improve data education
Is your data team established, but you can see expansion may be needed in future? Why not approach data training providers to offer consultative insights, gratis?
There are two angles to this:
1) Good PR and the potential for well-trained entry-level data staff funnelled to you on a priority basis
2) You are contributing to the betterment and education of future data professionals; arguably a social Good
Senior data staff from your organisation could deliver talks to university students, or work with course providers to improve the data science offering. Many degree-level courses leave graduates with an excellent theoretical and mathematical understanding of data. What they lack is real-world opportunities for application.
Quick links
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Big Red works on a project-by-project basis, using a structured and time-bound approach to hiring. Looking for jobs in data? Search Jobs today.
