Senior Design Analyst2019 - PRESENTStatistics New Zealand
Technologies: R, Python, SAS, Analysis, Statistics, Data Visualization, Data Processing, Machine Learning, Software Development
- Developed a data pipeline and output tool to get economic, health, and social data out to the public within weeks of the New Zealand COVID-19 lockdown. This solution was highly generic, scalable, and fit for purpose, and is still in production now.
- Developed a framework for building a processing system with a large number of business rules. This framework enables analysts to build business logic in a robust way, with a test framework around all parts of the system.
- Raised the technical capability of other staff through training and mentoring.
- Redeveloped the Indicators Aotearoa website as a Shiny R application. This improved the ability for this application to be kept up to date, with a clean metadata-driven approach to managing the content and robust pipelines for the data it presents.
Design Analyst2019 - 2020Statistics New Zealand
Technologies: R, RStudio Shiny
- Produced a statistical model for estimating the expenditure of international visitors to New Zealand based on electronic card expenditure. This model had to be rushed into production when traditional survey methods were not possible in 2020.
- Built a data processing pipeline for hundreds of millions of records from electronic card expenditure data. This involved data cleaning, fuzzy matching, aggregation, and visualization.
- Developed a visualization tool for New Zealand's import and exports in goods and services. This made a large and detailed data set easy for users to view, download, and understand.
Software Engineer2018 - 2019Verizon Connect
- Developed a React application for customers to visualize and manage their data.
- Maintained, fixed bugs, and developed new features within a large legacy codebase, alongside dozens of other developers. This required working in an Agile environment, writing tests, and carefully managing changes.
- Maintained and contributed to a C# application which provided search functionality to end users via a REST API.
Doctoral Candidate2015 - 2018Imperial College London
Technologies: Advanced Physics, C++, Python, Data Visualization, Bayesian Statistics, Statistical Methods, Computational Physics, Presentations, Technical Writing
- Independently led a study into the computational methods used to compute higher-order quantum corrections to dark matter particle masses. This resulted in two lead author publications, conference presentations and a sophisticated piece of software.
- Published the statistical study of a particular class of dark matter models as the lead author. This involved developing and running computational physics code in production on some of the world's largest supercomputers.
- Tutored undergraduate students, attended international conferences and meetings, spent working visits at a number of universities, and collaborated with other scientists around the world.
- Made major contributions to a novel study of statistical sampling algorithms for high energy physics. This involved running managing production scans using a range of different algorithms and different dimensionalities to draw meaningful comparisons.