At the New Zealand Energy Efficiency and Conservation Authority (EECA) I contributed to the development of the TIMES-NZ 2.0 energy model, a critical model for shaping the future of New Zealand’s energy system. This model enables the creation of detailed energy use scenarios across all sectors of the economy, offering valuable insights into the potential impacts of different policies and economic conditions.
My contributions included calibrating the model, running custom simulations, maintaining the application that visualizes the model's results, and most importantly collaborating with a large number of stakeholders and energy experts. I also authored essential documentation, both internal and public-facing, including a comprehensive guide that outlines the model’s structure, assumptions, and data sources.
Understanding the transport sector is essential to New Zealand. Transport affects how people live and move, it shapes the overall economy, and significantly contributes to emissions. At the New Zealand Ministry of Transport, I created data-driven solutions, including dashboards and automated reports, that improved decision-making and transparency. These tools streamlined internal processes and made critical transport data easily accessible to the public.
My work involved extracting and analyzing key data from sources such as the New Zealand Crash Analysis System (CAS), the Annual Motor Vehicle Fleet Statistics, and the New Zealand Travel Survey. These datasets are essential for understanding trends, improving safety, and shaping policies that impact all New Zealanders.
The data products I created followed best practices in data science, including developing reusable modules in R and properly packaging the code. This approach ensured the long-term usability of the tools which are still deployed in production environments.
Before transitioning into the data space, statistics and programming were central to my academic work. During my PhD at Victoria University of Wellington, I focused on researching sustainable materials for solar panels, testing these materials through ultrafast laser spectroscopy and collecting and analyzing the experimental data. My PhD thesis helped understand how charge photocurrent is generated in thin layers of Organic Photovoltaics (OPVs), which is important for improving the photovoltaic efficiency of these devices.
My master’s thesis focused on advanced numerical methods to study how water molecules ionize when exposed to intense, ultra-short laser pulses. This research required a strong understanding of quantum mechanics and was valuable for building fundamental knowledge of water ionization, which is important for fields like medical physics and radiation science.
In addition to my professional experience, I have been an active volunteer in my community. I was an organiser for R-Ladies, an initiative to support and encourage women in data science using the R programming language. And I ran a coding club at Karori Library in Wellington as part of Code Club Aotearoa, where I taught kids how to code in a fun and engaging way.
As a PhD alumni, I also volunteered to deliver a workshop introducing children to programming using Scratch, a visual programming language.
I believe writing is one of the best ways to learn from experience, connect ideas, and filter the most important information. It’s also a powerful tool for sharing knowledge and sparking meaningful conversations.
Over the years I’ve published various blogs, and I currently run a Substack called think data lab, where I explore topics like data science, analytics, and open data in a clear and accessible way.
My goal is to share insights from a data professional’s perspective, helping leaders and decision-makers better understand the value of data without needing a technical background.