The need for data science skills is driving demand for a new set of roles in 2020. Understand what they are, what they do and where to find the talent.

It is not news to talent acquisition teams that the demand for data science skills is disrupting the job market. Research by the World Economic Forum (WEF) in collaboration with Burning Glass Technologies, LinkedIn and Coursera is shedding light on how data science talent is being developed and deployed across today’s labour market, and their findings should be ringing alarm bells for TAs and hiring managers.

In the first wave of digitisation, data was largely seen as a by-product of the functioning of digital applications, operating systems and platforms. Now sensors are everywhere – we all carry smart phones which are mobile sensor platforms generating data. Cities are measuring a wide variety of data sources and governments at all levels are opening their data to their citizens. Increasingly, data is recognised as a significant asset enabling further innovation across ancillary fields such as artificial intelligence (AI), which can drive the improvement of services through process efficiency and deliver better results for customers.

Every day globally, 500 million tweets, 294 billion emails and 65 billion WhatsApp messages are sent, 4 petabytes of data are created on Facebook, 4 terabytes of data are created from each connected car and 5 billion searches are made. By 2025, the WEF estimates that 463 exabytes of data will be created each day – the equivalent of almost 213 million DVDs.

This proliferation of data has fuelled a meteoric rise in the demand for workers with skills in data science. All TAs know that the shortfall in data science skills supply is widening and intense competition between industry, academia and the public sector for such talent has created a high premium on such skills. Further, the WEF makes the point that the skills shortage has not only hampered individual business growth, but has reduced the capacity of whole industries and entire economies to leverage fully the dividends of innovation.

Studies by IBM, Forrester, LinkedIn and Tech Republic reach similar conclusions regarding the most in-demand data science jobs expected in 2020. Importantly, emerging vacancies for the jobs listed below are not limited to the IT sector as data’s importance grows across multiple sectors, including media and entertainment, financial services and professional services. 


The need for data science skills in 2020 is driving demand for these 10 roles:


Network analyst
Businesses are investing more heavily in their networks as IoT enters the workplace. Network analysts in the coming years will combine their technical skill set with an understanding of how to apply it to provide real-time trending information on network traffic, and what those insights means for the business.

Computer vision engineer
The professionals who build and improve computer vision and machine learning algorithms and analytics to detect, classify, and track objects. Global investment in these technologies is forecast to reach $215 billion in 2021, impacting directly the demand for computer vision engineers.

Machine learning engineer
Advanced programmers who develop AI machines and systems that can learn and apply knowledge. In coming years all companies will be impacted by AI and as that happens, AI will need to become a top investment area for any tech department.

Security analyst 
Cybersecurity professionals are already in great demand, and that will continue into the future, as attacks grow more sophisticated and technologies to fight them advance.

Cloud engineer
As the vast majority of companies move important systems to the cloud, more and more are choosing a hybrid approach, with multiple vendors. In the coming years, cloud engineers will develop solutions at scale that are a mix of both in-house technology and outside systems.

App developer
Across both end users and vendors, app developers will be in large demand in 2020. This will become a higher-level role than simply coding, according to Forrester analyst Andrew Bartels. “The developer may be someone who identifies a need and designs what the code would look like, and sends it off to someone else to do the actual coding.”

Business intelligence analyst
BI analysts gather data from a number of sources, including internal software, competitor information, and industry trends to develop a sense of where the company stands in the industry and how they can both grow and cut costs. The business analyst starts with the business side, and considers what the company needs in terms of apps to make the process work.

DevOps lead
As more app developers and business analysts come on board, DevOps teams will also need to be expanded to oversee and coordinate work between those groups. These professionals bring skills in development and project management that are required in many companies, even outside the context of software development.

Database administrator
The demand for this role will continue to grow, particularly as companies move toward more software offerings that include AI, and the ability to create AI-powered models. Forrester researcher Nate Meneer says: “Having well-maintained databases is really the secret to allowing those products to work effectively.”

User support specialist
As technology becomes deeply integrated into the operations of business units, more employees will need assistance from support specialists, especially as the workforce transitions, Meneer said. “As companies go through digital transformations, suddenly they find their operations increasingly interwoven into these systems. You’re going to need the professionals who can support that.”

Bridge the skills gap and find the talent you need:

The WEF says the rapid growth and evolution of data science roles and skills stresses the need for appropriate business strategies and education and training policies that can match this demand, in quantity and quality, so that skills shortages do not hinder the transformation potential unveiled by vast sources of data and improved data analysis techniques.

Clearly this is easier said than done. However, several strategies are available which can assist TA’s in bridging the skills gap.

Firstly, rethink the workforce ecosystem
Make increasing use of a diverse workforce ecosystem—a blended workforce where the traditional employee-employer relationships are augmented with all forms of alternative work arrangements, including freelance workers, contract workers and gig workers. Today, more and more professionals are opting for flexible working arrangements, and companies actively engaging with this increasing pool of on-demand workers are seeing their vacancies being filled quicker than their competitors.

Secondly, connect with talent marketplaces
Choose the right partners and targeted digital platforms which give you access to talent marketplaces where active and passive candidates are already vetted. The best of these platforms not only give TAs the ability to source and engage with talent marketplaces, but can integrate with a company’s core HCM technology and vendor management system to onboard, manage and track permanent and freelance workers, leading to a more complete view of the entire workforce.

Finally, think longer term beyond today’s immediate talent needs
In the Fourth Industrial Revolution, all sectors will need to undergo a fundamental transformation to fully absorb the potential dividends of the data economy. Such transformations will need to be accompanied by appropriate talent investments in data science skills.

Learn more about these strategies in our whitepaper and "Rethink your hiring strategies to attract and retain top non-permanent talent."