Data on a screen

The COVID-19 pandemic has taught us many things. This global crisis has meant that experts across many disciplines have had to address problems and propose solutions. One area that has been crucial to understanding and measuring the pandemic is that of data science. We take a look at why this field is so essential to our day-to-day lives and what the future holds for data science. 

As well as exploring the current landscape in the industry, we’ll also take a look at what drives growth and where the jobs are. We’ll examine the various routes into data science and the salaries on offer. 

The current landscape in the data science industry

In essence, the field of data science focuses on analysing data to provide insights and then using algorithms and machine learning to make informed decisions and predictions. In a world where we’re each producing more data than ever, it’s essential that we understand and manage the implications of this information. 

What is the data science industry’s global market value? 

There are several reports we can look at to get a measure of the global value of the data science industry. According to Grand View Research, in 2019,  the global data science platform market size was valued at $3.93 billion. Other data from Statista shows that in 2021, the global big data market is predicted to be worth $64 billion. 

When it comes to data analytics, another key area of data science, research shows that North America accounted for the largest market share in 2019, with a market value of just over $10 billion. Europe was the second-largest market in 2019, valued at around $6.43 billion. 

What is the data science jobs market like?

The role of data scientist is one of the most in-demand jobs in both the UK and the US. The role appeared on LinkedIn’s 2020 Emerging Job Report in both countries, featuring at number 3 in the US and number 7 in the UK. In the US, the role saw a 37% annual growth. The report also highlights that ‘data scientists may be augmenting responsibilities traditionally done by statisticians as some industries, like insurance, gear up for the future.’ 

Data from IT Jobs Watch shows that, in the six months to March 2021, there were 2,273 permanent data science jobs posted in the UK, down from 3,162 in the same period the previous year. A similar trend was seen in the US, where job postings for data scientists appeared flat between 2019 and 2020. 

However, this dip could easily be explained by the impact of the COVID-19 pandemic. Other data from 2020 shows that there was a shortage of around 250,000 professionals with security and data science skills, showing a clear demand for those with the right skills. 

Estimated growth 

Pandemic aside, the data science industry is still expected to grow over the coming years. Many sources have predicted that the sector and those adjacent to it will see a sustained increase in value. Looking back at the Statista data we mentioned earlier, the big data market is expected to be worth $103 billion by 2027, more than double its expected market size in 2018. 

This growth is also predicted in the data science platform market. Grand View Research suggests that the industry will see a compound annual growth rate (CAGR) of 26.9% from 2020 to 2027, providing an eventual revenue value of $25.94 billion.

Along with this market value increase, we’ll also likely see an increase in data science jobs. The US Bureau of Labour Statistics predicts a 15% rise in industry jobs between 2019 and 2029, much higher than the 4% national average.  

Although estimates for other countries are hard to come by, the projected growth in market revenue and jobs in the US suggests that this will be a trend seen on a global scale. 

What is driving growth in data science?

There are several factors that are contributing to the growth of data science and analytics. These relate to both the industry itself and wider trends in society. Here are some of the main growth drivers in data science at the moment: 

  • We’re creating more data. Some estimates suggest that 1.7MB of data is created every second by every person on average. This information can be harnessed for all sorts of purposes, from marketing to healthcare. What’s more, the data we produce is becoming more complex and detailed, meaning there is a need for those who can understand and interpret it. 
  • Our technology is improving. Data science touches on many other areas. Technology such as machine learning, artificial intelligence, and cloud computing all require data scientists and analytics. These emerging technologies will continue to grow and develop, as will the demand for those who can implement them. 
  • There is a need for informed decision making. Businesses of all kinds and sizes are turning to data to make decisions. The insights offered by data science can be invaluable, allowing organisations to make informed decisions about the future. 

Data science job insights 

Now that we’re familiar with the industry as a whole, let’s take a closer look at some of the jobs and careers in data science. Given the scope and demand for data insights, it’s not surprising that there are a variety of different roles in and routes into the field. We’ve outlined some of the main ones, along with salary data, below: 

What types of data science jobs are there? 

The principles of data science can be applied in many different fields. As such, there are quite a few different roles within the industry. We’ve picked out a few of the most popular and in-demand data science jobs at the moment: 

  • Data scientist. Professionals in this role analyse large amounts of complex raw data and process it to find patterns to help benefit a business or organisation. Data scientists use an array of technical skills to help drive strategic business decisions.
  • Machine learning engineer. This role sits somewhere between software engineering and data science. Machine learning engineers create data funnels and provide software solutions, and as such, need programming and data science skills.  
  • Data engineer. Data scientists will often rely on data engineers to create and maintain the data ecosystems that they use. It’s a role focused on the processing of gathered or stored data to create an effective pipeline. 
  • Data architect. This role is all about creating blueprints for data management systems. Data architects will assess an organisation’s data sources, and then work to design the systems that integrate and protect them.

What is the average data science salary?

Salary data tends to vary across the industry depending on the role and sector that you’re working in. However, there are some sources that provide a glimpse of the industry as a whole. Again, using IT Jobs Watch data, we can see that the median annual salary (50th Percentile) in the UK is £65,000. 

For the role of data scientist specifically, the figure varies between sources. Glassdoor puts the average data scientist base salary at £45,000 based on 1,440 salaries. For PayScale, this figure sits at £40,386 based on 1,169 salaries. Jobs site Indeed suggests an annual base salary of £53,404 based on 2,000 salaries. 

According to 2019 data from the US Bureau of Labour Statistics, the mean average salary for those working in data science is $100,560. 

How to get into data science

As well as a love for data, those working in the field of data science often must have a detailed understanding of mathematics, statistical knowledge and advanced computer skills. Given this broad set of requirements, there are several ways to enter the data science industry: 

  • Education. Most data science roles require a bachelor’s degree in a relevant discipline. Computer science, data science, mathematics, and statistics are all popular choices. A postgraduate degree specialising in data analytics or big data could also help. Data science certification is in high demand, and there are many data science boot camps available.
  • Experience. Those who can demonstrate experience in the relevant areas may also find it possible to enter the industry, even without formal qualifications. If you have a working knowledge of  R, Python, C, Java or Microsoft Azure and have strong database skills, you could find opportunities.
  • Internships and graduate schemes. Many organisations offer formal training to graduates or those with the right skill set. These can be a useful way of entering into the data science field. 

The future of data science

There is a lot of evidence to suggest that the data revolution is only just beginning. The most recent Big Data and AI Executive survey found that only 39.3% of companies are currently managing data as an asset. And while many are aiming for it, only 24.0% have created a data-driven organization. Over the coming years, these numbers are expected to increase. 

Similarly, although technologies such as AI and machine learning are now commonplace, there is a lot of scope for improvements and wider use in relation to data science.

As we’ve seen in the projected growth of the various associated industries, demand for data science jobs will remain high over the coming years. What’s more, all of the data science statistics we’ve covered here present a thriving industry with huge potential. 

Organisations are looking to significantly increase their data science headcount this year 

26th Jan 2021: With data science lauded as the answer to COVID-19 recovery, organisations are planning to significantly increase their data science headcount this year. This is according to the latest research from Le Wagon, an educational leader in data science bootcamps. 

Some of the key drivers for this increase in demand from organisations include the fact that businesses are looking to increase operational efficiency, develop potential new revenue streams and to grow existing capabilities. 

The research — which surveyed Le Wagon alumni in addition to UK employer partners — discovered the importance of being equipped with the right skills required for the future, with over a half (64%) of data science course alumni stating that they chose to complete the course for this reason. It also highlights the opportunities that data science skills can bring, with just under a half (43%) saying they have benefitted from more career opportunities since completing a data science course. 

But despite an increase in demand from organisations for data science talent in 2021, and more people looking to further their careers by learning new skills, it’s clear from the research that there’s still an existing skills gap — with employer partners stating that it’s very difficult to recruit the right talent they need. 

With data science tools becoming more common across many sectors as a way of generating business insights, being able to use these tools and having an understanding of statistics and data analysis will become essential — highlighting the vital need to close this current skills gap.

With this in mind, Le Wagon has partnered with one of the world’s top universities, Imperial College London, to offer a new intensive, ten-week data science course that will teach the fundamental skills that employers are currently demanding, and will help professionals looking for new opportunities to start their career in data science.

This course, developed in partnership with the Data Science Institute at Imperial College London through Imperial Projects, is a full-time, online and immersive learning experience which will equip participants with the skills to explore, clean and transform data into actionable insights and to implement machine learning models from start to finish.  

Boris Paillard, CEO, Le Wagon, comments: 

“While data science skills have been sought by organisations for several years, the demand is only getting higher — especially now that many companies have had to accelerate their digital transformation projects in light of COVID-19. But becoming a data scientist requires a wide range of both technical and soft skills. By partnering with Imperial College London and bringing together a significant number of people with expertise in data science, we will be able to help teach the skills needed in an immersive, unique online format.”

Dr Mark Kennedy, Co-Director of the Data Science Institute and Director of Imperial Business Analytics at Imperial College Business School added:

“We are excited about the new co-branded intensive data science course because it will offer the participants a rapid route to marketable skills which are now in high demand to a population who might otherwise miss out. In short, by attending this course you will go from the intention to learn new skills, from classroom to market.” 

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