Data science and decisions
Maths skills are essential for a data-driven future.
With its focus on specific problems, both real-world and abstract, university mathematics at UNSW Sydney gives students a solid grounding in analytical skills that are highly regarded in the workplace. Data science – one of the most in-demand skills for the 21st century – also relies on key maths concepts like algebra and calculus.
Computers and high-end software play an important role in maths at UNSW Sydney, and courses offer small-group tutorials so that all students get the right support.
The Faculty of Science has offered a brand-new degree in 2017, the Bachelor of Data Science and Decisions, a multidisciplinary program that will combine skills in mathematical methods and statistics with computing, business decisions and communication.
But maths is not just about data science – it also underpins nearly every major science project around.
Dr Gordana Popovic is a Statistical Consultant at UNSW Sydney’s Stats Central, where she supports internal research. “Almost all research, whether it’s in health, engineering or biology, requires statistics,” she says. “My job is to meet with people, hear about their research, and advise them on how to conduct the right analysis.”
On leaving school, Gordana enrolled at UNSW Sydney where she did a joint degree in maths and education, then after completing an honours year, did a PhD in statistics and statistical ecology. “Statisticians use maths to describe the relationship between different variables for data that has been collected,” she says. For example, you can use mathematics to look at information about rainfall, then build an equation that lets you predict how good the water quality is going to be.
Another senior statistician at UNSW Sydney, Australian Research Council Research Fellow Dr Peter Straka, is working on mathematical models for arrival times of extreme events, such as earthquakes and solar flares. “With my PhD student Ricky Gill, we write software to fit these models and perform statistical analyses to estimate the time and magnitudes of future extreme events,” Peter says.
After doing a five-year degree in mathematics in Germany, Peter graduated with a PhD in mathematics from UNSW Sydney in 2011, and has since worked as a postdoc in the US and the UK, before returning to UNSW Sydney as a researcher and a lecturer in statistics. “I’ve always loved maths,” Peter admits.
At present he is working with researchers from public health on a machine-learning approach to identify patients with depression, and on another project which identifies clinics as clusters in a network of medical doctors. “There is never a shortage of interesting projects,” he says.
Peter and Gordana are perfect examples of how maths can open the door for collaboration with researchers from pretty much any field that produces data.
– Fran Molloy