About me
I turn complex environmental and climate challenges into clear, actionable solutions by combining geospatial science, spatio‑temporal analysis and open‑source engineering. I support international development projects and teams in making robust, evidence‑based decisions that are reproducible, scalable and cost‑effective.
What I can do for your organisation
- Needs assessment & data strategy
- Systematic review of project goals and available data
- Tailored data roadmaps focused on impact and feasibility
- Systematic review of project goals and available data
- Custom open‑source tooling
- Automated, reusable analysis workflows that reduce manual work and risk
- Tailored solutions with full transparency and reproducibility
- Automated, reusable analysis workflows that reduce manual work and risk
- Cloud‑native geodata pipelines
- Scalable processing for large, heterogeneous datasets (satellite, sensor, socio‑economic)
- Modern deployments using Docker, distributed compute and cloud storage
- Scalable processing for large, heterogeneous datasets (satellite, sensor, socio‑economic)
- Knowledge transfer & workshops
- Hands‑on training in tool use, maintenance and extension
- Empowerment of your team to operate and evolve solutions independently
- Hands‑on training in tool use, maintenance and extension
- Monitoring & evaluation
- Interactive dashboards (e.g., Shiny) for operational monitoring and stakeholder reporting
- Continuous performance tracking and data‑driven decision support
- Interactive dashboards (e.g., Shiny) for operational monitoring and stakeholder reporting
Why clients choose me
- Project‑focused delivery that translates analysis into policy and operational actions
- Strong emphasis on reproducibility, open standards and long‑term maintainability
- Proven experience with international, interdisciplinary teams and donor environments
Core competencies
- Spatio‑temporal analysis of large, multi‑source datasets
- Open‑source software development and efficient geoprocessing
- Machine learning & deep learning (PyTorch, TensorFlow) for pattern detection and forecasting
- Database design & management (PostgreSQL + PostGIS)
- Interactive visualisation for decision‑makers (Shiny, Jupyter, Quarto)
- Agile delivery in international contexts
Technology stack (selected)
- Scripting & automation: Bash, Python, R
- Big‑data processing: Dask, GDAL/OGR
- Deep learning: PyTorch, TensorFlow
- Versioning & CI/CD: Git, GitHub/GitLab
- Development environments: Positron, VS Code, Quarto
- Web apps & dashboards: Shiny, Streamlit, Leaflet
- Databases: PostgreSQL + PostGIS, SQLite