In Summary

  • Professor Timos Sellis, Director of Swinburne Data Science Research Institute, discusses the growing demand for data scientists


Big Data equals big job opportunities. With organisations collecting more data than ever, skilled people are needed to understand how to analyse it and reveal the human patterns in the numbers. 

There is so much data out there and only a fraction of the information retained has been explored or collated for broader use. That’s changing.

“Organisations are aware they have been collecting data for monitoring their operations, staff roles, perhaps also for KPIs,” says Professor Timos Sellis, Director of Swinburne Data Science Research Institute.

“The difference now is people understand there may be more detail they can get out of the data they are holding and therefore more analysis and extraction of insights is of essence.”

Big leap in data technology

Technological change has always opened up skills gaps as education catches up with business needs. In the 1990s, as computing becoming increasingly vital to business, demand intensified for software engineers. As the internet was embraced and businesses wanted to present a public face online, website designers were all the rage.

In 2018, businesses are hungry for data scientists. Data scientists put together methodologies and technologies that will find useful patterns. They use Big Data to analyse all aspects of our lives— from traffic flow to providing holistic views of health over a lifetime.

“Data science is about people trying to use existing data in novel ways to gain insights into people’s lives,” says Professor Timos Sellis.

Professor Sellis says an example is universities analysing student data to understand factors behind student performance.

“We might need data on things like demographics, their Year 12 performance, and what students are saying online about their study experiences. Maybe they are not doing well in a certain subject because it is the first class after lunch; the weather may affect certain classes. The more data we have, the more factors can be considered, and we then have a better idea of potential problems contributing to an issue. Finding the unknowns is a challenge.”

Demand for high-tech skills

A recent report from StartupAus found people with high-tech skills are in short supply for the businesses that need them. These start-up phase roles include coders, business development and account managers, and user experience designers. As the business grows, they need product managers and data scientists.

“Organisations need people to help understand all the data they hold,” says Professor Sellis.

Previously, statisticians did the work of finding correlations between behaviours and outcomes. Now there are hundreds of different correlations, which presents a challenge when it comes to interpreting the sheer number of potential combinations of factors.

Data scientists have the capacity to work backwards. Instead of having a particular problem to solve and collect the data only on that problem, an organisation can set high-level goals and then analyse what needs to be done to achieve that goal.

Data science also has the potential to offer more personalised results. Medicine may be able to tailor a pill for an individual’s particular medical, physical and social profile, making treatments work more effectively for their specific biology and psychology. “Pharmaceutical companies are using data to drive this sort of analysis,” says Professor Sellis.

Data science at Swinburne

Swinburne is already bringing its data science expertise to industry partnerships, including working with drinks manufacturer, Asahi. The joint project analyses Big Data from Asahi’s production line to determine what events may lead to downtime, which affects productivity and costs.

Australian businesses, with vast seas of data, are feeding the surge in demand for data scientists and Swinburne is already moving to address the shortage.

In 2019, Swinburne plans to offer postgraduate education in data science, covering statistics, computer science, business, and design.

Professor Sellis says design in particular is an essential component of data science.

“People communicate by pictures. You need a visual interface to communicate the results. For example, the data showing accident rates and danger points in an area are better expressed as heat maps than numbers.”

Swinburne has also recently proposed a Centre of Excellence, in partnership with other universities, to look at the social aspects of Big Data.

“People, institutions, data and the machines that process and make decisions with the data all blend together,” says Professor Sellis. “We need to examine how this interacts with our social rules on issues like trust, security, privacy and governance.”

Professor Timos Sellis is part of the Data Science Research Institute.

Find out how Swinburne is leading the data-to-discovery pathway for data-intensive research and addressing grand challenges in industry.