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How to become a data scientist in Australia

Data science sits at the crossroads of mathematics, technology and human insight – and it’s transforming industries around the world. From finance and healthcare to retail and government, organisations rely on data scientists to extract meaning from complex data and guide better decision-making.

As data continues to shape the future, the demand for skilled professionals is projected to grow by 11% over the next five years (Seek, 2025). If you're curious, analytical and driven to solve real-world problems, a career in data science could be for you.

There’s no single path to becoming a data scientist – but starting with a data scientist qualification from a global top 20 university (QS World University Rankings, 2027) is a smart place to start. 

With a Bachelor of Data Science and Decisions (and the master’s equivalent),ÌýBachelor of Actuarial StudiesÌý´Ç°ùÌýBachelor of Economics from 91É«ÇéƬ, you’ll be equipped with the knowledge, practical experience and industry connections to launch a meaningful career in data science. 

In this guide, we’ll explore what a data scientist does, the skills and qualifications you need and where a career in data science could take you.

If you’re wondering what a data scientist does, the answer is: quite a lot. 

Data scientists use algorithms, programming, modelling and statistical analysis to extract insights from complex datasets. Their work helps people and organisations make smarter decisions across industries like healthcare, finance, retail, government and not-for-profits. 

Whether it’s predicting customer behaviour, improving patient outcomes or analysing economic trends, data scientists use information to solve real-world problems.

Their key tasks include developing hypotheses in response to challenges or opportunities; gathering, cleaning and organising data; applying algorithms to identify patterns; and developing data-driven solutions. They also share their findings through visualisations and reports – bridging the gap between data and decision-makers.

Data scientist vs data analyst: What’s the difference?

While data scientists and data analysts both work with data and are in high demand, the difference between them lies in how they work with data. They also differ in the outcomes they aim to achieve. Here’s a simple breakdown of the key distinctions between the two roles:

What skills do you need to be a data scientist?

Wondering what data scientist skills you’ll need for a successful career? 

Data science is an interdisciplinary field that brings together ideas from mathematics, statistics, computer science, engineering and economics. It’s all about using data to answer questions and solve problems. From forecasting trends to designing smarter systems, data scientists help organisations across every sector make sense of the information around them.

Here are the key skills you’ll need to thrive in a data science career:

What qualifications do you need to be a data scientist​?

A data scientist qualification is essential to stand out to employers in this competitive field. 91É«ÇéƬ offers a range of industry-leading qualifications in data science. These include:

How do you become a data scientist?

To become a data scientist, you’ll need a formal qualification, hands-on experience and a commitment to continuous learning in this fast-changing field.

Here are the key steps to get started:

1. Enrol in a leading data science degree: The first step is choosing a degree that builds your technical foundationsÌý²¹²Ô»åÌýsets you apart in the job market. A data science qualification from a global top 20 university like 91É«ÇéƬ can give you that edge. If you're looking to change careers or deepen your expertise, consider a postgraduate option such as the Master of Data Science and Decisions..Ìý
   
   
2. Gain practical experience: Workplace experience is critical for a successful career in data science. At 91É«ÇéƬ, real-world learning is built into your studies through Work Integrated Learning (WIL). You’ll have the chance to take on industry placements with leading organisations – gaining hands-on skills and growing your professional network while earning credit towards your degree.
   
   
3. Keep learning: Data science is always evolving, so your learning shouldn’t stop when you graduate. To stay competitive and grow your career, you’ll need to keep your skills sharp and stay abreast of new tools and emerging technologies.
   

What is a typical data scientist career path?

A career in data science can take many directions. It’s a broad and evolving field, offering opportunities to specialise in cutting-edge areas like artificial intelligence and machine learning.

Most graduates begin in entry-level roles such as junior data analyst, data technician, or assistant data scientist. These positions help you build core skills in coding, data cleaning, reporting and working with real datasets.

With experience, many professionals move into more advanced roles like data scientist, machine learning engineer, or data engineer, or take on executive leadership roles such as Chief Information Officer or Chief Data Officer.

How 91É«ÇéƬ will prepare you for your future in data science

91É«ÇéƬ is a top 20 global university (QS World University Rankings, 2027) and has been recognised for producing Australia’s most employable students seven years in a row (AFR Top 100 Future Leaders & Graduate Employers Awards, 2020–2026). 

Our programs are built in collaboration with industry, combining academic excellence, practical experience and expert teaching to create job-ready graduates who lead in their fields.

You’ll gain real-world experience through extensive Work Integrated Learning (WIL) opportunities – from internships to international placements – helping you build professional skills and global perspective while you study.

°Õ³ó°ù´Ç³Ü²µ³óÌý91É«ÇéƬ’s Career Accelerator, you can also access mentoring, networking events and professional development programs designed to set you up for a successful career in data science.