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?<\/p>\n\n\n\n
Interesting fact: The latest Future of Jobs Report from the World Economic Forum<\/a> suggests that data science is the skill with the largest shortage. And, of the 19 identified \u2018top cross-cutting, specialised skills of the future\u2019 more than half included data and AI as an emerging job cluster.<\/p>\n\n\n\n That\u2019s because data is being generated at an exponential rate across the world, and every industry in every country wants to capture and use data.<\/p>\n\n\n\n So, if you\u2019re thinking about a data science degree, read our top 10 questions and answers about being a data scientist.<\/p>\n\n\n\n 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 \u2013 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.<\/p>\n\n\n\n Is it really a science? Yes, because data scientists adhere to the scientific principles that all scientists do \u2013 experimenting, testing, validating. You might think we\u2019re geeky (most of us are proudly geeky) but more importantly, data scientists are explorers. We\u2019re at the frontline of advances in science and technology. For example, data scientists and mathematicians at Â鶹ֱ²¥ helped create an innovative security system<\/a> that developed into a suite of products for the company icetana<\/a>.<\/p>\n\n\n\n Data scientists collate and analyse data to provide new information to stakeholders \u2013 the people who will benefit from the information. Basically, we look at datasets to find patterns (usually the ones we\u2019re looking for and sometimes ones that are a total surprise) and we can create models to predict future trends.<\/p>\n\n\n\n Here\u2019s 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\u2019d provide the information that helps the government establish or revise a policy, and keep their data secure.<\/p>\n\n\n\n Good news: the latest stats from Seek<\/a> are that the average salary for data scientists in Australia is $110,000 \u2013 $130,000 (which is well above the median full-time salary of about $68,000<\/a>). Great news: jobs for data scientists are predicted to continuing growing by 13% over the next five years!<\/p>\n\n\n\n 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!<\/p>\n\n\n\n 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\u2019re always on the way to solving a challenge. In fact, the Australian Government\u2019s latest National Skills Commission report shows that the demand for data science jobs increased more than six-fold<\/a> in just four years.<\/p>\n\n\n\n Being a data scientist means that you\u2019re 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<\/a> 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.<\/p>\n\n\n\n Sure, we code, but not every day. It\u2019s more like we know how to code if we want to \u2013 we use programming languages like SQL, R and Python to automate tasks and get the job done quicker.<\/p>\n\n\n\n Some data scientists love coding and specialise in creating new algorithms and pushing the boundaries of machine learning. Here\u2019s another industry solution that resulted from great data science: The Marine division of Australia\u2019s 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\u2019s northwest shelf. There are many variables involved in such a large operation, but a Curtin team did the maths<\/a> and created new algorithms that helped to improve the company\u2019s operations involving the support vessels.<\/p>\n\n\n\n They\u2019re similar, because data analysts and data scientists both work with data \u2013 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 \u2018story\u2019 of the data in a meaningful way. Modelling using high-performance computers is commonly done by data scientists.<\/p>\n\n\n\n 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 \u2013 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.<\/p>\n\n\n\n Here\u2019s some of the big industries that employ data scientists:<\/p>\n\n\n\n Most data scientists have completed a uni course, like Â鶹ֱ²¥\u2019s Bachelor of Data Science<\/a>. Curtin\u2019s course combines theory studies with hands-on learning \u2013 which means that you graduate with both the scientific and technical knowledge and the practical skills to start work as soon as you\u2019re done studying.<\/p>\n\n\n\n When you complete the course, you\u2019ll 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\u2019s why data science is said to be \u2018highly interdisciplinary\u2019 \u2013 because you can apply your expertise to every discipline and every industry.<\/p>\n\n\n\n It’s the start of a great career as a data scientist! It\u2019s the formal qualification you get after completing a uni course in data science, like Curtin’s Bachelor of Data Science<\/a>. 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 \u2013 which is handy for networking and getting a higher-level job with a higher salary.<\/p>\n\n\n\n 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<\/a> or a full bachelor degree<\/a> in data science. Plus, if you study a Bachelor of Data Science<\/a> at Curtin, you can double your career power with another qualification, like a Bachelor of Commerce<\/a>, Bachelor of Engineering<\/a> or a Bachelor of Arts<\/a>. You could also do an honours degree \u2013 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.<\/p>\n\n\n\n1. What is a data scientist, exactly?<\/h2>\n\n\n\n
2. What does a data scientist do?<\/h2>\n\n\n\n
3. How much can I earn as a data scientist?<\/h2>\n\n\n\n
4. Are data scientists in demand?<\/h2>\n\n\n\n
5. What skills do data scientists have?<\/h2>\n\n\n\n
6. Do data scientists do coding?<\/h2>\n\n\n\n
7. Is a data scientist the same as a data analyst?<\/h2>\n\n\n\n
8. Who needs data scientists?<\/h2>\n\n\n\n
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9. How do I become a data scientist?<\/h2>\n\n\n\n
10. Can I do a data science degree at Curtin?<\/h2>\n\n\n\n