Join us at this event to hear different perspectives of what a career in statistics looks like. We'll have a handful of Early and Mid career statisticians, working across academia, industry and government, talking about their experiences. The speakers have been invited to share their journey, what they've learned, what they've enjoyed, and what mistakes they've made along the way.
Each speaker will give a 10 minute talk, followed by a panel discussion of about 30 minutes. There will be an opportunity for socialising and networking afterwards, with catering.
Will Mackey is an applied microeconomist at Commonwealth Treasury, currently on a secondment from Grattan Institute. An economist and data scientist, his work has covered migration, tax incidence, higher education. He spent 2020-21 working on Australia’s COVID-19 response with Grattan and in the Victorian Department of Health. Will runs workshops on data analysis, communication, and visualisation, is the founder of the R users network for Australian public policy (runapp), and is the author of a number of R packages for public policy.
Dr Anna Quaglieri
Anna has an academic background in Statistics, completed between the universities of Bologna, Glasgow and Melbourne. Once in Melbourne, she joined the WEHI where she did her Masters research in Population Genetics, and PhD in Cancer Genomics. She then worked for 1.5 years as a Data Scientist for the AI consulting company Eliiza. Over a year ago she joined the Melbourne based startup Mass Dynamics as Bioinformatics Data Scientist. At Mass Dynamics Anna develops workflows for the analysis of mass spectrometry data, with the aim of helping more life scientists transform proteomics data to knowledge.
Dr Michael Couch
Michael is a mathematical physicist (PhD Northwestern University) turned machine learning engineer and developer of data-rich applications. His interest is in the engineering side of data science: how do we shift good data science code out of RStudio and Jupyter Notebooks and put it into robust automated training and testing pipelines, manage hands-off deployment of models, and allow for on-demand batch and realtime predictions.
Dr Susan Wei
Susan Wei is a lecturer in the School of Mathematics and Statistics at the University of Melbourne. She currently holds a Discovery Early Career Researcher Award (DECRA) from the Australian Research Council (ARC). Her research interests include statistics, machine learning, and deep learning. She is part of the Melbourne Deep Learning Group.
Dr Swen Kuh
Swen is currently a Research Fellow in Statistics at Monash University working in collaboration with Columbia University in the United States. Her research area includes hierarchical modelling, Bayesian methods and inference, and applications to social science. Before her PhD, she worked briefly in a market research company after finishing her studies in both sociology and statistics at the University of Auckland, New Zealand. Swen is also now serving as the Deputy Membership Officer for the Statistical Society of Australia, Victoria branch (SSA Vic). Outside work, she enjoys travelling, photography and trying out new recipes.