WHO & UNICEF Data Systems (Pulilab)
Data-intensive Python systems for global development organisations — partnering directly with WHO and UNICEF stakeholders.
International development organisations needed reliable, data-heavy platforms — and the work meant translating requirements directly from WHO and UNICEF project stakeholders into delivered systems.
- 01
Built a Python data-management platform for WHO and maintained UNICEF frontend reliability for a global user base, delivering a 1.5M-word content-management system end-to-end.
- 02
Designed a Scrapy data-enrichment pipeline for 20,000+ medical clinics — automated extraction of images, contact data and entity information at scale.
- 03
Architected a 100,000+ datapoint analytics system with multi-level aggregation (city / country / global), geolocation processing and statistical outlier detection.
- 04
Built an OpenAI-powered content-strategy system with automated A/B testing — pre-ChatGPT, in 2021–22, as part of an AI early-adopter arc going back to 2018.
- 05
Owned the deployment lifecycle: Docker containerisation, CI/CD, full-stack across Django REST APIs / PostgreSQL and Nuxt.js / Vue.js, with reporting in Jupyter / Pandas / NumPy.
Delivered the systems international stakeholders relied on, end-to-end — from data pipeline through API and frontend to the deployment that ran them.
- Django
- PostgreSQL
- Scrapy
- OpenAI
- Nuxt.js