As someone already established in data science, I didn’t want to do something that covered a lot of things I already knew. I think it is very desirable to have a postgraduate degree or qualification in the data science field.
I chose the Master of Mathematical Sciences as it would allow me to deepen my understanding of the concepts underpinning modern data science and also let me learn many new things.
I am currently working at the Australian Securities and Investments Commission (ASIC) as a Senior Data Scientist and have been since starting the degree.
I currently manage analytics project and staff, some of which are studying their undergraduate degree. I also previously worked in consulting in analytics at PwC.
Previously Richard completed the Bachelor of Engineering (Chemical) and Bachelor of Commerce, and won the University Medal for his honours work in econometrics.
I have always been interested in quantitative subjects and my first-year advanced maths subjects were amongst the ones I enjoyed the most.
Whilst I have covered many mathematical topics in my chemical engineering and commerce degrees, it is good to look at things with an extra degree of rigour in the School of Mathematics and Statistics.
The content of the courses I have done so far has covered some really interesting things: from topical issues such as the modelling of infectious disease and climate modelling, to the mathematical underpinning of data science staples of neural networks and singular value decomposition.
It has also been interesting to see topics covered in my previous degrees from a new perspective, such as the link between random walks I saw in commerce and diffusion mechanics covered in chemical engineering.
I am hoping that my masters degree will give me a competitive advantage in allowing me to step to a new level of management.
I wish to move further into advanced analytics and modelling and how these techniques can provide value to a wide range of applications and stakeholders.