I am a data professional with experience working in both modeling and engineering focused roles. No matter which side of the fence I’m on, I love writing clean, modular, well-organised code to solve challenging data problems. I am completely comfortable writing production-ready code in R and Python, and have a good deal of experience designing and maintaining SQL databases.
Outside of work, I am an active contributor to the open source software community, having developed or made large contributions to a number of R packages. I’m also an avid reader, particularly of philosophy, and a keen (though not very good!) rock climber.
I am currently shared between the data and statistical methods teams, spending half my time in each. This being the case, I work on a fairly wide variety of things.
On the one hand, I am responsible for carrying out various statistical procedures (e.g. weighting, small area estimation, propensity modelling, forecasting) and writing technical reports.
On the other hand, I am the technical lead on a variety of software engineering projects, typically focussed on data modeling, integration, processing, analysis and reporting, but often general application development. Some of the things I’ve worked on in this latter capacity are:
I was the lead data engineer on the SES, which approaches hundreds of thousands of higher education students each year.
I was in charge of the community operations team, which was responsible for ensuring that the application marketplace was running smoothly.
Alongside managing 15+ casual staff, I
| 2019 | Hastie Prize in Philosophy, the University of Melbourne |
| 2016 | Peter J. Lloyd Prize in Theoretical Physics, Monash University |