I'm a data scientist and economist and I use data to help people make sense of a complex world and make better decisions. My work is robust, transparent, and reproducible, and I provide responsive and personal service. I have a PhD in economics and 15 years of experience as a consultant.
Analysis of big and small datasets including geospatial and time-series data.
Forecasting using trends or bespoke statistical models.
Predictive analytics and causal inference, to aid decision-making.
Industry analysis to study how markets work.
Data visualisation and data communication for clear and engaging presentation.
The tools I use include R, QGIS, Mapbox, SQL, Excel, and D3.js.
Some examples of my recent work:
Airport forecasting: I developed econometric models to produce forecasts of passenger and aircraft volumes for major airports in Australia and one potential new airport. These projects involved estimating and testing econometric forecasting models in R, and using those models to build interactive forecasting tools in Excel.
Interactive data maps: I worked with Figure.NZ to create a set of maps to show social and economic data for New Zealand. This required geospatial analysis and creating custom Mapbox map themes to visualise the data.
Transport revenue forecasting model: New Zealand's Ministry of Transport asked me to review and improve the model that it uses to forecast billions of dollars of government revenue from fuel taxes and excise duties. This involved updating econometric forecasting models and improving a complex forecasting tool.
Water demand analysis: The water utility in a major city asked me to analyse drivers of water demand, including spatial differences in demand across the city and estimated effects of changes in water pricing. This involved collating data from disparate sources to use in econometric analysis.
Spatial population and movements analysis: I have worked on several projects involving the analysis of population distribution and movements of people and tourists based on very large spatial datasets. This work involved large-scale data processing, cleaning, and analysis, and the design of static and interactive data visualisations.