Are you thinking about a career in statistics and data science? Currently in a degree or looking to make a career shift? Join us at Zendesk's offices 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 and industry, talking about their current work and experiences.
Each speaker will give us a 10-minute overview on their current work and how they got there and answer some of your questions. Following the talks, there'll be time for attendees to socialise and ask more questions. Food included!
Speaker bios
Ximena Camacho
Ximena Camacho is a third-year PhD candidate specializing in the use of linked population-level data to assess the safety of prescription medicines. Her research focuses on using real-world data to examine long-term outcomes and adverse events related to medicine usage in routine clinical practice. Through her work, she strives to generate policy-relevant evidence that supports the needs of medicines regulators and policy makers and ultimately improves health outcomes.
Ximena has over a decade of experience in health services research. By applying sophisticated methods to linked administrative data, she provides valuable insights that inform health system planning, policies, and clinical decision-making. Ximena has held a variety of analytic and leadership roles and collaborates regularly with clinical, government and academic partners, both locally and internationally.
Naryman Tarvand
Naryman is a Data Scientist at Biarri and works primarily on forecasting and optimisation problems. Naryman works with clients from a range of industries to produce solutions to their business problems, which often translates to saving money or time. Naryman is passionate about applying the technical math knowledge to solving real world problems.
Floyd Everest
Floyd is a PhD student at Monash University in the faculty of Econometrics and Business Statistics. Floyd's research centers on statistical election auditing, specifically focusing on ranked voting elections. Floyd is also interested in modern hypothesis testing techniques incorporating bayesian models.
Damian Pavlyshyn
Damian Pavlyshyn is postdoctoral researcher in the disease elimination program of the Burnet Institute, where he works on the causal analysis of observational data. The diversity of data available at the Burnet and the ubiquity of researchers wanting answers to causal questions have allowed Damian to work in a broad range of applications, including Hepatitis C elimination, housing and incarceration, and HIV genomics.
These research topics have been a departure from Damian's graduate studies - Damian completed his PhD in Statistics at Stanford University in 2022, where he studied random matrix theory and optimal estimation in high-dimensional data. Though this work had been largely theoretical, Damian was able to apply it in unexpected fields, such as ancient Roman history and fly breeding.
Rheanna Mainzer
Dr Rheanna Mainzer is a Biostatistician at the Murdoch Children’s Research Institute. She is currently working on developing and evaluating methods for handling missing data in large-scale longitudinal studies. She also provides statistical leadership for studies undertaken by researchers in the areas of respiratory health and preterm birth.
@StatSocAus
