Data scientists: what is it like to be one and what do they do?

Data science may be dubbed the ‘sexiest job of the 21st century,’ but what is it actually like to be a data scientist in today’s world? With data shaping everything from healthcare breakthroughs to the latest entertainment trends, data scientists are at the heart of some of the most exciting innovations happening right now. 

To uncover what makes this field tick, we spoke with Dr Chao Chen, a seasoned data scientist and researcher with over a decade of experience in data science and machine learning.  

Dr Chen, who completed both a Bachelor of Information Technology (now known as a Bachelor of Computer Science) and his PhD in Information Technology at Deakin, offers a firsthand look at what it’s like to be part of this fast-moving profession – and what aspiring data scientists need to know to thrive. 

What is a data scientist? 

In the simplest terms, data scientists are the problem-solvers of the digital age. They collect, analyse and interpret complex datasets to help businesses make smarter, more strategic decisions.  

Think of them as data translators: blending statistics, programming and business savvy to solve real-world problems. 

And the best part? They get to work on a different challenge every day. One moment, they could be cleaning up data; the next, they might be building algorithms or presenting their findings to stakeholders – ensuring the insights they uncover are both relevant and actionable. 

For many data scientists, it’s this curiosity about data and the desire to dig deep for valuable insights that makes the role so rewarding. 

As Dr Chen, who’s worked with major brands like Telstra, puts it: ‘What led me to become a data scientist was my curiosity about data. I love digging deep to uncover valuable insights and enjoy presenting these findings — it gives me a real sense of fulfilment.’  

What does a data scientist do? 

A day in the life of a data scientist is anything but dull. They’re the ones asking the big questions, examining the data and using machine learning to predict future trends.  

Whether it’s uncovering hidden patterns in customer data, improving product quality or helping businesses make smarter decisions, data scientists are always in the thick of it. 

Data scientists excel at turning raw data into actionable insights. They apply statistical methods and machine learning to sift through massive datasets, detect trends and forecast what’s coming next.  

But it’s not just about crunching numbers. Data scientists also need to think strategically and make sure their findings lead to practical, real-world solutions that have an impact across the business. Collaborating with different teams is a key part of the role – it’s all about turning data into change. 

Dr Chen reflects on a regular day: ‘I start by checking my inbox and setting priorities for the day. I also meet with stakeholders to discuss their needs or present the insights or models I’ve worked on. Then, I get my hands dirty with the real technical stuff, such as creating predictive models. Sometimes I do presentations within the whole team to share the insights I find too.’ 

Do data scientists code? 

Yes, coding is an essential part of the job.  

Data scientists are highly skilled in programming, using languages like Python, R and SQL (Structured Query Language) to manipulate, analyse and visualise data. Coding isn’t just for creating algorithms — it’s also used to automate repetitive tasks and optimise processes, freeing up time for more creative and strategic work. 

While not every task will involve coding, it’s still a core skill that enables data scientists to extract insights efficiently and effectively. It’s the foundation upon which they build the models and tools that power business decisions and innovations. 

Are data scientists in demand? 

You better believe it: Data science is officially recognised as a top-tier career in Australia, with data scientists among the highest-paying and most in-demand.

In fact, a recent review of the state of data science in Australia suggests that the global market for data scientists is expected to grow almost 10-fold over the next five years. 

This rapid growth is driven by the increasing need for data to inform smarter decision-making across every industry from healthcare to finance to tech. With more and more data being generated every day, skilled data professionals are more sought-after than ever. 

Roles in the field span a wide range of specialisations, including machine learning engineer, data analyst, quantitative researcher and business intelligence specialist.  

Is artificial intelligence going to replace data scientists? 

With artificial intelligence (AI) moving at lightning speed, it’s natural to wonder if data scientists could one day be replaced by machines.  

While AI can automate repetitive tasks like data preparation, visualisation and even some predictive modelling, it doesn’t have the critical thinking and strategic decision-making that human data scientists bring to the table. 

Data scientists are all about context – they interpret the data and align it with an organisation’s goals and values. So, far from replacing data scientists, AI is becoming a powerful tool that helps them work more efficiently.  

By automating routine tasks, data scientists can focus on what truly matters — refining complex models, guiding AI projects and developing insights that drive business growth. 

Do data scientists get paid well? 

Short answer: Yes. Data science is one of the most lucrative careers in tech. According to SEEK, data scientists in Australia earn an average annual salary between $115,000 and $135,000. 

Entry-level positions start at around $74,000, while experienced data scientists can earn up to $151,000 annually, reflecting their specialised skills and the high demand for their expertise.  

Freelance or contract roles typically pay between $58 to $61 per hour, making data science not just a rewarding career intellectually but financially, too. 

With high demand, growth potential and competitive salaries, data science is a career that promises both fulfilment and financial reward. 

How to become a data scientist in Australia 

Data science is a dynamic, rapidly evolving field — and the good news is, it’s open to people from all kinds of backgrounds.  

Whether you’re just starting out or transitioning from another career, there are plenty of ways to break into the field. 

How long does it take to become a data scientist? 

Becoming a data scientist is a journey — but it’s one with massive rewards. The first step is typically earning a bachelor’s degree in a relevant field, such as computer science, mathematics or IT. This usually takes about three years of full-time study. 

To level up and set yourself apart, many data scientists pursue further education. Dr Chen shares: ‘My PhD study and degree contributed the most towards me getting this job. The training I received during my PhD study dealt a lot with data analytics and machine learning. Also, the degree I completed proves that I am qualified to do this kind of job.’ 

Graduate certificates or master’s degrees in data science offer advanced expertise, opening doors to leadership roles. Graduate certificates take a few months to complete, while a master’s degree can take one to three years, depending on study load. 

It’s not all about qualifications, though. Gaining hands-on experience is key. Aim for internships while studying to build your practical skills, grow your portfolio and expand your professional network. Entry-level roles, such as data analyst or business analyst, can give you the industry experience you need to launch your career as a data scientist. 

What are the skills required to become a data scientist? 

Data scientists are more than just tech whizzes. They blend technical expertise with a knack for problem-solving and storytelling. Here’s what you need to succeed: 

Programming: Python, R, SQL — these are your essential languages for handling large datasets and building models. 

Statistical analysis: Understanding statistics is crucial for extracting insights from data. 

Machine learning: Creating algorithms to predict trends and automate processes is central to data science. 

Data visualisation: Tools like Tableau and PowerBI help you present data in a way that makes sense to decision-makers. 

Communication: Data scientists need to be able to explain complex findings to non-technical audiences. 

Dr Chen emphasises the importance of ‘strong SQL skills, machine learning and coding to create predictive models, and mining values from big data assets, and strong communication skills to explain your work to the business.’ 

Can you be a data scientist without a degree? 

Absolutely. While a degree provides a solid foundation, it’s your skills, experience, and ability to solve problems that truly matter. Many successful data scientists have built their careers through alternative paths, focusing on hands-on experience, online courses and certifications. 

What sets top-tier data scientists apart isn’t just the credentials — it’s their ability to apply their knowledge in real-world situations, think critically and continuously evolve with the field.  

So, if you’re self-motivated, curious and ready to learn, don’t let the absence of a formal degree hold you back. 

The challenges (and rewards) for data scientists 

Like any career, being a data scientist comes with its challenges. The sheer volume of data, the complexity of problems and the pressure to make fast decisions can be daunting. One of the biggest hurdles is effective communication.  

Dr Chen explains, ‘What I like most about my job is also the biggest challenge: communication with business stakeholders. I must explain the models with no technical terms. Otherwise, nobody can really understand me.’ 

However, the rewards far outweigh these obstacles.  

As Dr Chen continues, ‘the thing I love most about my job is the creative work and the communication with business stakeholders. Creative work keeps me from becoming a dull man! Staying close to the business means I get to work with people, not just machines.’ 

Data scientists thrive on solving complex problems, using their skills to make an impact in their organisations and industries. Overcoming challenges like messy datasets or ambiguous questions is part of what makes this job so exciting. 

What it’s like to be a data scientist: key takeaways 

So, what’s it like to be a data scientist? It’s a fast-paced, ever-evolving career that blends analytical thinking, problem-solving, and the thrill of working with cutting-edge technology. 

Data scientists are the ones driving data-driven decisions that shape industries, spark innovation, and even tackle global challenges. Whether you’re spotting trends to fuel business growth or building models that push boundaries, your work will always be game-changing and impactful. 

If you’re someone who loves cracking complex problems, has a passion for coding, and gets excited about turning data into real-world solutions, data science might just be your perfect match.