About

Phil's background is in geography and economics. He spent about ten years in spatial and economic analysis across public health, transport and urban policy, starting as a spatial data analyst on children's urban health research at SHORE, Massey University, where he co-authored five peer-reviewed papers. At MRCagney he worked on the National Policy Statement on Urban Development Capacity analysis, using regression to model the effect of zoning regulation on land prices.

From there his work moved into data science and then data engineering. As a spatial data scientist at Geographic Business Solutions he deployed and configured enterprise geospatial platforms for clients. At the Ministry of Health and then Te Whatu Ora he automated geospatial workflows, kept public-facing map layers current, and built nphsintel, an R package that gives analysts one route into population health data. At AA Insurance he developed the pricing emulator used in the migration to a new policy platform and advised on the architecture of the analysis platform.

He is currently focused on integrating AI into data practice: bringing AI into how data platforms are built, tested and used, while keeping the data current, tested and well governed. He also built and runs his statistics API, eolas.

Phil has always enjoyed programming, and he cares about doing it well: packaged and tested code, reproducible analysis, automated reporting and shared standards that let a team work the same way.

Phil leads every engagement and reviews every client deliverable.

Clients own what we build. The code and run history stay with you, and the work is documented so you are not dependent on us.

Phil's CV and writingLinkedIn