Data science jobs & careers
Technological advancements have placed data at the forefront of every business, making it invaluable for business analysis and decision-making. With a postgraduate degree of data science in Australia, you gain the skills to gather data and view the world with a more nuanced lens, turning you into an incredibly important asset to business leaders and decision-makers. Careers in data science have topped LinkedIn’s job list in the Emerging Jobs report for three years running with an annual growth rate of 37%, making it one of the most in-demand careers of the 21st century.
Data science is a broad field that is constantly evolving alongside technology, it has grown to include various jobs and career pathways. Appealing to individuals experienced or interested in IT, mathematics and problem solving, a data scientist requires a critical and analytical mindset. Data scientists are continuously working to expand the capabilities of data extraction and machine learning – they are asking new questions on how far we can push technological advancements. Conversely, data analysts find meaningful insights and trends within datasets – they look to find answers to the questions raised by data scientists. Data science roles can overlap and change, however, there are specific categories within this field and it is useful to know which role will best complement your skills and interests.
Types of data scientist jobs & pathways
Whilst these are a few key career paths within data science, the possibilities are limitless. The industry is rapidly growing, and different roles are constantly emerging. If you’re wondering how to land a data science job, the answer is there are a few different routes. Students undertaking data science come from a diverse range of backgrounds, from business and economics to science, IT and engineering – data science and data analytics are a multifaceted field. Studying an online Graduate Diploma of Data Science with Monash University can keep you relevant in this fast-moving world of data as you’ll be learning from the largest group of academic experts in the APAC region.
Data scientist
Expected salary in Australia: $110K – $130K
Data scientists explore and forge the path in this multidisciplinary field and seek new ways to obtain data through computer science, predictive analysis, statistics and machine learning. They can specialise in a specific field or keep their skills broad and manage intersecting projects. Data scientists are constantly making technological breakthroughs and establishing new areas of study within the industry. This position requires problem-solving skills and creativity to lead data into the future.
Key responsibilities:
- Identify data sources and automate collection processes.
- Build predictive models and machine-learning algorithms.
- Propose solutions and strategies to business challenges.
- Collaborate with the engineering and product development teams.
Data analyst
Expected salary in Australia: $85k – $105k
A data analyst is someone who works with data to provide insights, identify key figures and present relevant information to enhance business decisions. They are trained to locate strengths and weaknesses, through the collection of information, and identification of patterns and trends from data pools.
Data analysts require good technical skills and are not only able to identify patterns within data but also transform their findings into a data strategy and actionable insights that can be understood by stakeholders. Being an excellent communicator and having the capability to present findings is a crucial element of the role. Data analysts take large-scale information and transform it into important and concise findings.
Key responsibilities:
- Collecting and interpreting data about relevant topics of importance to businesses.
- Analysing results and reporting the insights back to the business.
- Maintaining databases.
Statistician
Expected salary in Australia: $80k – $95k
For people who love working with numbers, statisticians process and analyse data through mathematical means; collecting, managing and interpreting numerical sets. Statisticians develop useful business predictions. From financial and operational forecasts to patterns in consumer behaviour, they extract projections from data trends while having a strong understanding of programming languages such as R or Python. Their unique and in-demand skills are required across different industries. Seek highlights that statisticians work across the public and private sectors with data science jobs in government departments, financial institutions and technology companies.
Key responsibilities:
- Collect, analyse and interpret data to produce valuable statistics that highlight trends.
- Ensure that the method of data collection and the analysis methodology is valid, efficient and accurate.
- Making sense of data science with Python and R programming language.
- Record, present and represent data graphically, reporting on key findings.
Data engineer
Expected salary in Australia: $126k
Building the infrastructure to support all of the collected data, data engineers build informational systems to organise and store data, ensuring that everything is accurate. Data engineers work alongside analysts to build software solutions that will enhance the collection of such large data pools. This role is great for individuals who love programming and problem solving, requiring someone extremely detail-driven to ensure that complex systems are working simultaneously, and delivering the most efficient methods of data collection and data analysis.
Key responsibilities:
- Create and maintain efficient data pipeline architecture.
- Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, and re-designing infrastructure for greater scalability.
- Build the data infrastructure required for extraction, transformation and loading of data from a wide range of sources.
Machine learning engineer
Expected salary in Australia: $50k – $136k
Machine learning engineers (also called artificial intelligence engineers) work to create detailed systems and AI (artificial intelligence) that collect large complex data sets. With an extremely nuanced understanding of programming and machine learning, this role will create tools for data extraction. A machine learning engineer requires a strong background in engineering or computer science as they are not only understanding data but building the programs that house it.
Key responsibilities:
- Designing and developing machine learning models and deep learning systems.
- Running machine learning tests and experiments.
- Implementing appropriate machine learning algorithms.
Demand for data scientists in Australia
To pursue a career path in data science, individuals require specific technical and mathematical skills. However, there is a broad range of industries offering job opportunities for which you are in demand, allowing you to pursue personal interest areas. Data science jobs are expected to see an 11% growth in the next 5 years. As a result, data scientists in Australia and around the world have become crucial to business intelligence (BI) teams. Whether you are interested in sport, fashion or finance, data scientists work to pave the way forward.
Industries to note are:
- Global financial institutions
- Government organisations
- Technology start-ups
- Health
- Public administration and safety
These fields rely on data scientists to collect their information and process it to make advancements that will help the entire community.
Data science teams are now perceived as valued members of companies, a source of truth and direction when it comes to business decisions. They help to bridge the gap between the business and their consumers, taking masses of consumer data and transforming it into information and actionable insights that can ultimately help companies better serve their customers.
“The cool thing about data is that you can give the same data set to 100 different people and I guarantee everyone will find some new way to use the data or some new information they derive from the data,” says Data Scientist Seun Aremu, who is currently developing a machine learning framework dedicated to structuring asset data.
“You have to be comfortable with the unknown when working with data. You have to trust your skills and trust your research because you’re going into the deep end without knowing where the bottom is.”
With Monash’s 100% online Graduate Diploma of Data Science, you can gain credibility in your field and recognition of your expertise, employers will know that you have deep and well-rounded knowledge in data science.
Moreover, this degree can help you transition into new positions, upskilling and tapping into different areas of data and analytics could help you broaden your skillset and drive your career in data forward. Speak to one of our course consultants today to find out more on 1300 272 509 or arrange a booking online today.
