Last Updated on June 14, 2021 by Admin
We take a look at what the state of play is in the data science industry. You’ll find details about working in the data sector, including the types of roles, salaries, and skills you’ll need to get started.
Data plays an increasingly important role in our lives. Everything from our healthcare to our entertainment is driven by information produced by millions of people worldwide. As we continue to create data in greater volumes and on a larger scale, the data industry is growing. We take a look at everything you need to know about the current landscape.
As we explore this fascinating field, we look at some of the sectors, jobs, and challenges related to data. We’ll also cover some of the skills you’ll need to enter the industry, as well as how you can get started with a job related to data.
The global data industry
First, let’s look at what we mean by the term ‘data industry’, and what the current landscape looks like. This will help us get some context as to some of the global trends and what the future might hold:
What is it?
The data industry is large, touching on all kinds of different areas and sectors. As such, it can be hard to define the exact parameters of it as one industry. From relatively straightforward tasks like data entry to complex data science, the opportunities and applications related to data are vast and varied.
That being said, there are a few fields that stand out in particular. These areas will often overlap, but there is generally a high degree of specialisation and variety in each. Some examples include:
We’ll take a look at some of these areas and some relevant data jobs further down. As we’ll see, there are all kinds of roles that fall under these specialisations.
How big is the industry?
Given the data industry’s scope, it comes as little surprise that it’s a rapidly growing sector. Some figures suggest that, in 2018, the global big data and business analytics market was valued at $168.8 billion. This figure is expected to grow to around $274.3 billion by 2022, increasing by 13.2%.
A similar trend is seen in the world of data science. Estimates indicate that the global data science platform market size will be worth around $25.94 billion by 2027. This represents a growth of 26.9% between 2020 and 2027.
This increase in the value of the industry is also being seen in the demand for data jobs. One report from the UK’s Royal Society found that the need for professionals with specialist and big data skills more than tripled over five years, increasing by 231%. Similarly, in the US, the demand for data scientists increased by 344% between 2013 and 2019.
However, despite this incredible growth, there is a problem. Many sources report that there is a data skills gap. Across fields like data analytics and data science, there are reports of shortages of skilled professionals. What’s more, employers, in general, feel that their employees lack data skills, harming productivity.
How has the COVID-19 pandemic impacted the data industry?
The coronavirus pandemic has impacted just about every industry in some way. With lockdowns, remote working, and job losses felt around the world, conditions have been difficult. The same is true, in part, for the data industry. However, it’s not all bad news.
Data science and big data analytics have played a role in helping us track and understand the virus. As well as monitoring things like health system demands, the ongoing efforts for virus testing, data modelling, and contact tracing have helped turn the tide.
You’ll have no doubt also seen a lot of data visualisation related to the pandemic. Such efforts to present the facts and current situation in an easy-to-understand way have been crucial in keeping people informed. It’s also played a role in convincing people to change their behaviour – take ‘flattening the curve’ as an example.
Despite the successes of the industry, there are still some issues. According to the job site Indeed, in July 2020, US-based data science job listings were 43% below their 2019 levels. Other reports suggest that the global big data analytics growth is expected to be ‘restrained’ in the wake of the pandemic.
What kinds of jobs are there in the industry?
So, despite the current pandemic-induced climate, there is still a lot to be excited about by the data and analytics industry’s future. If you’re wondering about some of the data-based jobs you could get involved with, you’ll find plenty. The field is diverse, with new and exciting roles appearing frequently.
We’ve picked out some of the best data jobs across various niches to give you an idea of what’s out there. Of course, there may well be some overlap between these roles, and some may fall into multiple categories.
Data science jobs
Data science focuses on analyzing data for insights and then using algorithms and machine learning to make decisions and predictions. As you can imagine, a data science career can bring work in a whole host of different areas. Some data science roles include:
- Data scientist. This role focuses on processing raw data to create meaningful and insightful information. Across fields such as finance, science, healthcare, IT, and even the games industry, data science uses data to solve problems and help organisations make decisions.
- Machine learning engineer. By combining software engineering and data analysis, machine learning engineers create algorithms and programs to help computers learn automatically. Again, the applications for machine learning and deep learning are vast.
- Statistician. Professional statisticians are often problem-solvers. They collect, analyse, interpret and present information for businesses and big data companies across numerous industries.
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Data analysis jobs
While data science focuses on the end product of information, data analysis focuses on the inspecting, cleansing, transforming, and modelling of it. Professionals in this field still usually draw conclusions from the data, but also spend time processing it first.
- Data analyst. This role is similar to that of a data scientist, but often not as hands-on in terms of creating algorithms. Data analyst jobs exist to identify trends and present those findings in a way that’s easy to understand.
- Business intelligence analyst. BI analysts help organizations improve and overcome obstacles. They look at data to highlight weaknesses and use modelling and technology to propose solutions. It’s a role that’s increasingly in demand.
- Marketing analyst. This role is all about studying marketing conditions to determine what products and services a company should sell and to whom. They use data analytics skills to look at customer demographics, competitors, and market requirements.
Big data jobs
A career in the big data industry focuses on dealing with sets of information that are too large and complex to apply traditional means of data processing. In a world where we’re producing more data than ever before, there is a significant demand for people with data skills in this area:
- Big data engineer. Data engineer jobs often require professionals who can create and manage the infrastructure that deals with huge amounts of data. They work on the collecting, storing, processing and analysing of the relevant information.
- Data architect. A data architect focuses on building databases that handle large data sets. They work on the planning and integration of the databases, making sure they’re secure and accessible for those who use them.
- Database administrator. While a data architect creates the databases, a database administrator makes sure they run smoothly. They make sure they’re safe and backed-up, as well as helping to troubleshoot any issues.
How do data job salaries compare?
If you’re looking for a job in the data industry, you’ll probably want to know much such work pays. Given the variety across the roles, it comes as little surprise that data jobs’ pay scales differ significantly between positions, industries and locations.
In the table below, we’ve picked out a range of data industry jobs and the average salaries across several countries. Data comes from PayScale.
|Machine learning engineer||£50,584||$112,357||$76,663||$77,171|
What skills do I need to enter the industry?
If you’re hoping to get started with a job in data, there are plenty of opportunities available. As we’ve seen, the data skills demand is high right now, and that trend is set to continue. The exact skills and knowledge you’ll need will depend on your career aims. However, are needed no matter what role you’re aspiring to.
Usually, employers look for a combination of hard and soft skills in data job applicants. As well as demonstrating you have the applied knowledge to work in this field, you’ll also need to show a range of interpersonal and transferable skills.
This refers to the practical and quantifiable knowledge you need to do your job. Often, these are acquired through formal study and qualifications, although it is possible to learn them yourself. Some of the most relevant ones include:
- Structured Query Language (SQL). SQL is a type of programming language that’s designed specifically for managing data and databases. It’s a skill that’s useful for just about any role related to data.
- Python and other programming languages. Other programming languages are often required, particularly for data science and analytical roles. Python is always a good place to start, and Java and C/C++ are also useful.
- AI and machine learning. Predictive analytics are hot topics in the world of data right now. Skills in artificial intelligence and machine learning, particularly in relation to big data technologies, are highly sought-after.
- Data visualisation. It’s important to be able to present data sets in an easy-to-understand way. Skills in data visualisation can help you do exactly that, which is why they’re worthwhile learning.
These are the interpersonal and transferable skills that make you a good employee. They’re often less defined than hard skills, but employers look for those with strong soft skills. For data jobs, some essential ones include:
- Communication. Many types of data jobs require you to communicate your findings in terms that non-experts can understand. You’ll also have to work with a range of other professionals within your organisation. As such, good communications skills are essential.
- Critical thinking. As we’ve seen, data jobs tend to be highly analytical. By working on your critical thinking skills, you’ll be able to objectively analyse your data and ask the appropriate questions.
- Problem-solving. Many data roles focus on helping organisations identify and solve problems. Sometimes, knowing the right problem to solve is half the battle. It’s also a skill that can benefit you in both your personal and professional life.
- Collaboration. Those working in the data industry rarely work in isolation. You’ll need the skills and knowledge of other professionals if you’re to be successful. Teamwork and collaboration are vital to this success.
Why choose a career in data?
If you’re thinking of a career in the data industry but aren’t sure whether it’s for you, there are a few things to consider. Here are some reasons you might choose a data career:
- There’s a lot of demand. As we’ve seen, despite the current uncertainty in the world, the need for those who can understand, manage, and interpret data is high. This need for skilled individuals is expected to continue, meaning you’re likely to find work if you have expertise.
- It pays well. Average salaries, even for many entry-level positions, are generally quite high. There is the potential for you to earn a significant amount just about anywhere in the world.
- You can help people. As we’ve seen during the COVID-19 pandemic, data can be used to help people in many ways. By understanding trends and predicting patterns, you can help to anticipate and solve all kinds of issues.
- It’s future-proof. The data skills that you’ll develop are likely to last you your entire career. As we move to a more data-driven world, you’ll hopefully find a lot of career security in this sector.
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How to get started in the data industry
So, you’re hopefully now eager to move into the data industry, but where should you start? Thankfully, it’s a career that can have many starting points, although this depends on the exact role you’re hoping to move into.
As with many industries, you’ll usually need a combination of skills and experience to get a job in data. We’ve outlined some of the ways you can get your data career started:
- Education. Whether it’s for data analyst skills or data scientist skills, you’ll need to spend some time studying the relevant material. Many top-paying data roles require at least an undergraduate degree, while others may even ask for a master’s degree. That being said, you can gain knowledge in key areas through your independent learning.
- Training. Formal training usually takes the form of an internship or placements. However, through your own projects and learning, you can gain many of the data skills you’ll need in your career.
- Experience. Having some industry experience is often vital to securing a role in data. Again, this can come with a placement or your own projects. However, you could also gain exposure to data roles through your current job through a secondment or similar.
- Networking. Knowing the right people often helps in securing a new job. By expanding your professional circle and learning how to network, you can make new connections in the data industry.
Clearly, the world of data is a fascinating and varied one. There are many exciting job roles and careers out there, and demand for such positions is high. Whether you want a career in data analytics, a career in data science, or a career in big data, there are many skills you can work on to achieve your goals.
As the world becomes a more data-driven place, many of us will need to know how to analyse and interpret data. So, even if you’re not looking for a career change, working on your data skills can benefit your work and home life.
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