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Number of AI roles in Britain up 485% since 2014, Indeed reveals

The number jobs in artificial intelligence (AI) in the UK has risen dramatically in the last three years, according to Indeed.

Since 2014, the number of available AI roles in Britain has increased by 485% - representing a significant spike in demand for employees with the appropriate skills for the job.

Yet Indeed’s data also reveals there are over two times as many AI jobs available than there are suitable applicants, with a ratio of 2.3 roles available per candidate searching in the last quarter. Interest in AI roles has risen more steadily by 178% in the past three and a half years, not quite high enough to meet the fivefold surge in postings.

The popularity of software in innovations including smart home devices and customer service chat bots demonstrate how the industry is developing at pace.

Typical roles in AI include machine learning engineers and software developers in areas as diverse as banking, universities and commerce. In most cases applicants require previous experience and a degree in a subject like maths or physics, although some may even have qualifications in machine learning. But despite the sector paying well - the average annual salary for a machine learning engineer is £54,366 - the availability of workers with suitable skills simply isn’t keeping up with demand from employers.

While the Government has made high profile attempts to encourage more people take up science, technology, engineering and maths (STEM) subjects and degrees, Indeed’s data reveals that this has yet to feed through to the AI front line.

Mariano Mamertino, EMEA Economist at Indeed, commented, ‘’Employers in every sector are keen to utilise artificial intelligence and need workers with the right skills to fill these roles. Our data shows that competition for this shallow pool of candidates is fierce, with the numbers of available roles outstripping potential new hires.

“The AI sector is likely to keep growing as the potential for the widespread application of the technology, across different industries, becomes more clear. Investing in education and the right skills needed to propel the industry forward will be key to its growth in the coming years.”

  • Michael Segal, area VP, strategy, NETSCOUT, said, “Job site Indeed yesterday revealed that there are twice as many jobs in artificial intelligence (AI) as there are suitable applicants, highlighting a huge skills gap that the UK will need to urgently address.

“This is fueled by the complex job requirements for machine learning (ML) and AI professionals. With machine learning relying heavily on mathematical algorithms and programming languages such as R, Phyton, MATLAB, and Octave, prospective hires should have both software development experience and solid mathematical knowledge.  This combined skill set is unfortunately not easy to find.

“Further complicating matters, prospective hires should also possess subject matter expertise in the specific industry or field in which they will work.  Here’s why:

“Teaching machines how to learn from their own experience is an iterative process, as data scientists constantly fine-tune the machine learning models in response to ongoing data analysis.  They build training data sets for this process, which must contain attributes that are relevant for a particular field. To build a good data training set for medicine, for example, a data scientist should have expertise in medicine.  This holds true across many machine learning algorithms, such as supervised and unsupervised learning, anomaly detection, and recommender systems.

“This is the reason why finding the perfect talent is so challenging. To address this urgent issue, ML and AI studies should be developed as a new engineering discipline, with industry expertise being added later. Once new graduates are hired, they should then be trained in the specific field of the hiring corporation, so they can become experts in their respective field.”

  • Doron Youngerwood, product manager digital intelligence of Amdocs, stated, “As enterprises, and especially service providers, start to embrace AI, there undoubtedly needs to be a change in skill sets, processes, cultures and accountability.

“A data science (DS) talent or prospect should hold a mixture of mathematics and statistics knowledge, along with programming skills and business understanding, specifically expertise within the chosen industry. Unfortunately, finding these elements in one person is almost impossible. So the recruiter or HR departments wishing to plug their own company’s skills gap should pay attention to the main benefit the new talent will bring to the company.

“In a company where there are programmers to support data scientists there is a need to recruit talent with deep knowledge in algorithms and a very good business understanding of how data can be used to enable AI.

“In the meantime, a company where there are no programmers or other data scientists, the recommendation would be to bring in talent that has general programming skills, preferably with a focus on statistical programming (which broadly can be found in programming languages such as Python or R) and SQL (Structured Query Language), until the skills gap itself is closed in other ways, and those programmers can then learn to adapt their knowledge to the specific business area. ”

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Tags: Indeed AI

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