Windhoek, Namibia
Quantitative climate
intelligence from the ground up.
I build statistical pipelines that translate physical climate hazards into infrastructure investment risk — designed from the start for data-sparse African markets where existing models quietly fail.
About
I'm a quantitative analyst and the founder of Quantil Risk CC — a climate finance venture building auditable, open-source risk pipelines for infrastructure assets across southern Africa.
My background is applied mathematics and statistics, with Honours research in extreme value theory applied to Namibian wind speed data. I work at the intersection of climate science, spatial analytics, and development finance.
I'm working toward graduate study in climate finance, targeting leading UK programmes — building the published work and experience to get there.
Work & projects
Namibian Climate Risk Sandbox
An open, reproducible pipeline combining NOAA ISD station data, CMIP6 projections, and OS-Climate's physrisk-lib to produce boardroom-ready physical risk assessments for Namibian infrastructure assets. Designed to demonstrate the full chain from raw climate data to climate-adjusted NPV.
Modelling Wind Speed Extremes Using Extreme Value Theory: A Case Study for Namibia
Applied Peaks-Over-Threshold and Generalized Pareto Distribution methods to model extreme wind speed events using Namibian meteorological station data. Produced return-level estimates with uncertainty bounds directly applicable to renewable energy infrastructure siting and insurance pricing.
Automated data pipelines for urban development research
Engineered end-to-end data pipelines connecting KoboToolbox field collection to Power BI reporting via Power Query API, eliminating manual handling across multi-site development programmes. Built spatial maps in QGIS and interactive dashboards for programme impact monitoring.
Data visualisations
Tableau Public visualisation — coming soon
First visualisation: Namibian wind speed return levels from Honours thesis data.
Build in Tableau Public → Publish → paste the embed code here.
Skills
Statistical & mathematical
Data & engineering
Climate & finance
Currently learning
Writing
Why Namibia's weather stations are a development finance problem
Twenty stations, 825,000 km², and every DFI risk model assumes dense observation networks. What that actually means for infrastructure lending in southern Africa.
Extreme value theory for people who finance African infrastructure
A practitioner's explanation of return periods, tail risk, and why the 1-in-50-year flood is the number your lenders care about most.
Building a climate risk pipeline with open data: a Namibian case study
NOAA ISD + CMIP6 + physrisk-lib — step by step, in Python, reproducible. Everything a development finance team needs to validate physical risk for a Namibian infrastructure asset.
Currently
- Building Quantil Risk CC — quantitative climate risk venture, Windhoek, Namibia
- Studying BSc Hons Applied Statistics — NUST (graduating 2026)
- Learning Python for climate data pipelines, Yale Financial Markets (Coursera), Wharton Finance & Accounting
- Targeting Graduate study in climate finance — leading UK programmes
- Reading Coles (2001) — An Introduction to Statistical Modeling of Extreme Values
Contact
I'm always open to conversations about climate risk, development finance in southern Africa, data collaboration, or the graduate study journey. Reach out directly.