I'm a Data Science and Research Consultant based in Auckland, New Zealand. I partner with organisations to solve complex data challenges, especially in environment and ecology, using advanced data analysis, machine learning, spatial statistics, and generative AI.
My work involves transforming complex datasets into actionable insights, robust models, and strategic tools.
Machine Learning & Predictive Modelling
- End-to-end model development, from feature engineering to deployment and clear interpretation of results.
Time-Series & Spatial Analysis
- Specialising in complex, location-based and time-dependent data to uncover deeper, contextual insights that standard analyses miss.
Cloud Data Architecture & Pipelines
- Designing and implementing efficient, scalable, and reproducible data analysis workflows.
Statistical Consulting & Research
- Providing expert experimental design, rigorous statistical validation, and clear technical reporting for major initiatives.
| Project | Description | Technologies |
|---|---|---|
| Time-series modelling analysis | Developed and benchmarked a suite of time-series models (from ARIMA to ML ensembles) to predict ecological outcomes using a messy public dataset, providing clear guidance on model selection under differing scenarios. | R, Python, Scikit-learn, git |
| Spatial Network Design | Designed a spatially-optimised sampling network for vegetation monitoring, using spatial statistics to maximise data quality while minimising operational costs. | R, SQL, QGIS, git |
| Conservation Technical Report | Undertook analysis and modelling and authored a comprehensive, data-driven ecological baseline and technical report for a major conservation management initiative in New Zealand. | R, SQL, Quarto, git |
I'm always open to discussing new projects or consulting & contracting opportunities. If you're facing a data challenge that requires deep analytical expertise, let's connect.
- LinkedIn: [www.linkedin.com/in/craig-eric-simpkins]