We get school students asking us questions like: what does a data scientist do? are data scientists in demand? how much does a data scientist earn? Wow, that much … so how do I become a data scientist?
Interesting fact: The latest Future of Jobs Report from the World Economic Forum suggests that data science is the skill with the largest shortage. And, of the 19 identified ‘top cross-cutting, specialised skills of the future’ more than half included data and AI as an emerging job cluster.
That’s because data is being generated at an exponential rate across the world, and every industry in every country wants to capture and use data.
So, if you’re thinking about a data science degree, read our top 10 questions and answers about being a data scientist.
1. What is a data scientist, exactly?
A data scientist is a specialist who dives into data, to produce new information that can solve problems, or improve business operations, or even help create amazing innovations. The potential for data science to improve lives and create knowledge is massive – from how meteorologists predict storms, to the way that astronomers discover new galaxies, to how sports analytics help coaches optimise their player recruitment and game strategies, data makes a difference.
Is it really a science? Yes, because data scientists adhere to the scientific principles that all scientists do – experimenting, testing, validating. You might think we’re geeky (most of us are proudly geeky) but more importantly, data scientists are explorers. We’re at the frontline of advances in science and technology. For example, data scientists and mathematicians at Curtin University helped create an innovative security system that developed into a suite of products for the company icetana.
2. What does a data scientist do?
Data scientists collate and analyse data to provide new information to stakeholders – the people who will benefit from the information. Basically, we look at datasets to find patterns (usually the ones we’re looking for and sometimes ones that are a total surprise) and we can create models to predict future trends.
Here’s a basic example. Say a government wants to review how much the use of bike helmets has reduced the incidence of head injuries. Has it been significant? So, a data scientist or data analyst might design how the relevant data is collected, and check the data sets on accidents involving cyclists and compare the data on head injuries involving helmet-wearers and helmet-rebels. Then they’d provide the information that helps the government establish or revise a policy, and keep their data secure.
3. How much does a data scientist earn?
Good news: the latest stats from Seek are that the average salary for data scientists in Australia is $110,000 – $130,000 (which is well above the median full-time salary of about $68,000). Great news: jobs for data scientists are predicted to continuing growing by 13% over the next five years!
4. Are data scientists in demand?
Huge demand. Heard of big data? Digitisation of information has been increasing since the birth of computers, and data is being generated at an exponential rate across the world. And as big data has become more available, organisations have been hiring data scientists to source and analyse the data to improve their products and get that edge over their competitors. Data delivers information, information creates knowledge, and knowledge is power!
Having data science skills in the IOT (internet of things) era is why data scientists are in demand and earning great salaries. And being a data scientist is very satisfying, because we’re always on the way to solving a challenge. In fact, the Australian Government’s latest National Skills Commission report shows that the demand for data science jobs increased more than six-fold in just four years.
5. What skills do data scientists have?
Being a data scientist means that you’re an expert in computer programming, simulation and data mining, so it’s a no-brainer that students who decide to study a bachelor of data science enjoy maths and tech, and love problem-solving. Data scientists think outside the box, to explore different data sets to create new information and knowledge. We like to discover unexpected patterns and correlations. We like working with computers (love supercomputers!) and customising our tech.
6. Do data scientists do coding?
Sure, we code, but not every day. It’s more like we know how to code if we want to – we use programming languages like SQL, R and Python to automate tasks and get the job done quicker.
Some data scientists love coding and specialise in creating new algorithms and pushing the boundaries of machine learning. Here’s another industry solution that resulted from great data science: The Marine division of Australia’s largest independent oil and gas company, Woodside, was looking to optimise the vessel operations involving transfer of cargo and oil between support vessels and tankers operating in WA’s northwest shelf. There are many variables involved in such a large operation, but a Curtin team did the maths and created new algorithms that helped to improve the company’s operations involving the support vessels.
7. Is a data scientist the same as a data analyst?
They’re similar, because data analysts and data scientists both work with data – collecting, analysing, looking for patterns and trends. But data scientists will do all that and more, turning the data into information that can be understood and used. A data scientist might visualise the data to present the ‘story’ of the data in a meaningful way. Modelling using high-performance computers is commonly done by data scientists.
8. Who needs data scientists?
Every industry in every country wants to capture and use data to create better products and services. As a data scientist you can pretty much pick any industry that interests you – population health, law, agriculture, engineering and countless others. And data science is a really flexible career. If your interests change, you can change your industry.
Here’s some of the big industries that employ data scientists:
- Space science and geographic information science
- Sport
- Defence and security
- Agriculture and environment science
- Anthropology and ancestry
- Law
- Resources and energy
- Transport and supply chains
- Health
- Education
- IT and media
- Artificial intelligence and robotics
- Economics, business and finance.
9. How do I become a data scientist?
Most data scientists have completed a uni course, like Curtin University’s Bachelor of Data Science. Curtin’s course combines theory studies with hands-on learning – which means that you graduate with both the scientific and technical knowledge and the practical skills to start work as soon as you’re done studying.
When you complete the course, you’ll know how to collate, analyse and make discoveries in data. With these data science skills you’ll be able to identify past trends and current trends and predict future trends, which is a vital part of the planning done by businesses in every sector and by all government departments. It’s why data science is said to be ‘highly interdisciplinary’ – because you can apply your expertise to every discipline and every industry.
10. Can I do a data science degree at Curtin?
It’s the start of a great career as a data scientist! It’s the formal qualification you get after completing a uni course in data science, like Curtin’s Bachelor of Data Science. The qualification is important because it proves to employers that you have the expertise to do the job. Plus, you usually need a qualification for membership of a related professional organisation or society – which is handy for networking and getting a higher-level job with a higher salary.
Curtin is known as a university of innovation, so of course it has researchers working in data science innovation and teaching a range of data science courses. You can study for an undergraduate certificate or a full bachelor degree in data science. Plus, if you study a Bachelor of Data Science at Curtin, you can double your career power with another qualification, like a Bachelor of Commerce, Bachelor of Engineering or a Bachelor of Arts. You could also do an honours degree – an extra year where you get to do an independent research project in a particular area, like cybersecurity. And after you’ve gained your undergrad degree, you could study for a postgraduate qualification in the specialist area of predictive analytics.
If you like the sound of data science but would like a second opinion, take the Find U Quiz!
