CAREERS IN DATA SCIENCE AND STATISTICS

Welcome to our first event of the year!

This event will showcase a panel of experts and discuss the different journeys that brought them to their current role in data science and statistics.

Doors will open at 5.30pm with pizza, drinks and networking. The panel discussion will start at 6pm.

Professor Di Cook
Dianne Cook is Professor of Business Analytics at Monash University in Melbourne, Australia. Her research is in the area of data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit. A current focus is on bridging the gap between exploratory graphics and statistical inference. Technology plays an important role in data visualisation for evaluating effectiveness and for public consumption. Di utilises technology such as virtual environments, Amazon’s Mechanical Turk, and eye-tracking in her work, and makes an effort to share her work with open source software. Di is a Fellow of the American Statistical Association, elected member of the International Statistical Institute, past-editor of the Journal of Computational and Graphical Statistics, elected Member of the R Foundation, and current editor of the R Journal. Education is an important part of her contributions, and mentoring graduate research is a significant activity. Several of her students have won the prestigious American Statistical Association John Chambers Software Award, including Hadley Wickham, Yihui Xie, Carson Sievert, and most recently, Monash student Earo Wang.

Dr. Lauren Smith
Lauren is a Postdoctoral Fellow in Infectious Disease Modelling at WEHI. Lauren has a broad range of interests spanning across One Health, human/veterinary/wildlife epidemiology, infectious disease and population dynamics modelling, and statistical analysis. Lauren currently works on projects relating to the control of infectious diseases in the Asia-Pacific region, including the development of diagnostic tools to identify individuals recently infected with Plasmodium vivax. In her previous research, she has addressed questions related to the management of animal populations and infectious diseases, and the welfare of domestic animals. This has included using statistical and mathematical models to assess the effectiveness of free-roaming dog population management, rabies control strategies, canine distemper virus dynamics, African swine fever in domestic pigs, and cetacean ecology and conservation.

Dr. Mun Hua Tan
Mun Hua is experienced in genomics and bioinformatics, with a hybrid repertoire of wet- and dry-lab skills. She is currently a postdoctoral researcher in the Day Lab at the University of Melbourne, focusing on malaria surveillance and antigenic diversity in natural parasite populations. Mun Hua holds a PhD in Life and Environmental Sciences and a Bachelor of Science in Biotechnology. Her areas of expertise include genome assemblies and annotation, variant calling, phylogenetics, genetics, data processing, and data visualisation. Mun Hua’s professional journey has included work experience in academic research, genomics centres, and industry, on a breadth of biological systems. She enjoys working in interdisciplinary collaborations, where she frequently navigates the intersection between biology and computational analysis.

Evie Gizem
Evie has extensive experience working in data science and analytics teams on various projects in the education sector, research, and government. Currently she is a Lead Data Analyst at RMIT, working in the Data & Analytics team. Evie holds a Master of Analytics degree from RMIT and a Bachelor of Science in Mathematics. Her areas of expertise include statistical modelling, machine learning techniques, data processing, programming, and data visualisation. Evie is passionate about effectively communicating data science concepts and provides guidance to both internal and external clients on data science strategies, utilising cutting-edge tools and approaches. She also evaluates the feasibility of data science projects to ensure practical outcomes are achieved.

Dr. Göknur Giner
Göknur Giner is a bioinformatician at WEHI. She has been using her statistical and machine learning skills to develop new bioinformatics methods needed for advancing genomic data analysis. In particular, she has been working to better understand the origins of the most invasive forms of breast cancer and to understand cancer metastasis. She has extensive experience working with and developing tools for genomic technologies, such as RNA sequencing, whole-exome sequencing, CRISPR/Cas9, microarray; and experiments conducted with circulating tumor cells, patient-derived xenografts.

See you there !