I work for Toi Hau Tāngata, the Social Wellbeing Agency (SWA). SWA is a small departmental agency shining a light on policy issues that affect the well-being of New Zealanders. Not all policy issues fit neatly within a single agency – this is where SWA comes in, collaborating across the system.
In the analytics team, most of our projects involve using Stats NZ’s Integrated Data Infrastructure (IDI), which allows us to study how – anonymised – people interact with different government agencies, over time.
I’m helping with a few different projects, for example, working with MSD to understand the vulnerability of older people. This involves translating ideas from existing research surrounding the vulnerability of older people into indicators we can quantify and study over time, using IDI data. I typically use R and SQL to prepare and understand the data I’m working with, before moving into visualisation and making our findings accessible to non-technical audiences.
I grew up in Tāmaki Makaurau, curious and idealistic. A lot of my thinking – then and now – stems from questions like “how can I make this better?” and “what is your experience [of life] like?”.
I started off studying engineering at uni. While I enjoyed the math and coding aspects, I found engineering restricting. I wanted to think holistically about environmental issues – and how they impacted people. I ended up majoring in economics, minoring in math and taking many papers – like anthropology, human geography, statistics, and GIS. I loved the balance of detailed, creative, and big-picture thinking – something I love now I’m working too.
I first came across SWA through the Analytics and Research in Government (ARG) internship programme (2020/21). Through a screening process, an agency is selected, and SWA was suggested to me. It was rewarding to apply what I’d learnt at uni to big-picture questions; understand kiwi’s interactions with government and explore ways to help everyone thrive. My curiosity and idealism had found their place. I decided to delay my master's until I had more experience and joined SWA as a grad (through the ARG graduate programme) this year.
Yes. At uni, I felt if I wanted to work as a data scientist, I needed to be a ‘coder’ – adopting an identity centred around computer specs, comparing programming languages and all sorts that didn’t resonate. The diversity of my team at SWA deflated those stereotypes. Our team has a range of different backgrounds – like statistics, computer science, and economics. Now I see that being a data scientist is more about being curious about data, open to learning and motivated to do right by the people your data represents. Internships are a great way to give something you’re unsure of.
I love working to make a positive difference in New Zealanders’ well-being and working with people with similar motivations. This shared vision, alongside SWA’s small size and supportive structure, creates an atmosphere of belonging. I’m also lucky to have mentors in projects, in my team, and in my manager, who encourage continual learning and foster a safe environment to grow.
My team is asked lots of great questions, some of which we’d love to research but can’t. There are time, data and expertise constraints. It doesn’t feel good to say no and disappoint people, especially when you understand and agree with their vision.
At the implementation end of the research process, data scientists are only one part of making change. Our research influences change, but this change is neither guaranteed nor instantaneous. The policy change comes about through a long, careful process.