Hola 👋 I’m a passionate data professional with academic and industry experience in data science and data engineering. In my work, I’ve used predictive analytics and AI/ML to solve real world problems that produce insights for organizations. I also enjoy crafting data visualisations to enable better data-driven decisions. I am certified in the following:
- AWS Certified Machine Learning – Specialty
- Databricks Certified Associate Developer for Apache Spark 3.0
- Advanced GitHub Actions
Currently, I work as a Data Engineer at Versent, mostly working around the Databricks ecosystem and PySpark. Some of the organizations I’ve had the pleasure to work with in the past include Multitudes, Wildlife.ai and Manatū Mō Te Taiao (Ministry for the Environment). I’m also a Fellow at the Good Data Institute, where we accelerate social and environmental impact by designing, developing and building data capabilities for not-for-profits. I have limited availability at the moment, but if you think my work could bring value to your organisation, feel free reach out by email or connect with me on LinkedIn and we can set up a chat. You can also meet my digital alter-ego on GitHub.
I’m very interested in a wide range of environmental and data/AI issues, including sustainability, climate action, data ethics, AI/ML alignment and using tech for good. If you are interested or invested in any of these topics, reach out to me and I’d be happy to have a catch-up.
My academic background is in computational cosmology. I’ve contributed to dark matter research by applying topological data analysis to numerical simulations of the cosmic web - the largest observable structure in nature. You can find my research paper here.
Offline, I like reading, discovering new music, and I love spending time outdoors (especially hiking, surfing, skiing and trail running). I also like to reflect on ways I can minimise my environmental impact. I’m always challenging and looking for ways I can improve the way I walk the talk (which is very far from perfect).