Acerca de Ghinwa
I build AI tools that help governments make data-driven informed decisions - with speed, reliable systems and accuracy.
My background sits at an unusual intersection: PhD economist, data scientist, and product manager. I've spent the last few years translating that into practice — designing GenAI workflows for various government bodies, building diagnostic AI prototypes at the World Bank, and leading a cross-functional team developing an AI policy tool with the Agency Fund. What I care about most is the gap between what AI can do technically and what actually works when you put it in front of a policymaker. Closing that gap is the job.
🌱 Outside of work, I enjoy hiking, climbing, and reading, remaining curious and always eager to learn more.
Inglés
Bilingüe o nativo
Español
Competencia profesional básica
Árabe
Bilingüe o nativo
Francés
Competencia profesional básica
Acepta trabajo presencial
Valencia (hasta 50 km)
Experiencia
- PolicyCopilotProduct Manager - Lead Data Scientistagosto de 2025 - Hoy (1 año)Product in active development in collaboration with the World Bank and The Agency Fund• Grew from Lead Data Scientist into Product Team Lead, managing a cross-functional team of 7 (3 engineers, 1 UX designer, 3 data scientists) across backend, frontend, and data science workstreams• Leading product development for an AI-powered diagnostic tool for policy practitioners, built in collaboration with The Agency Fund and World Bank, analyzing 20+ development outcomes including maternal health, youth unemployment, and education• Driving product decisions through structured feedback loops between knowledge base curation, UX research, and engineering — balancing practitioner needs against technical constraints
- o‑xAIPrincipal Data Scientistnoviembre de 2024 - Hoy (1 año y 9 meses)• Leading engagement with Frontier Tech Hub | FCDO: Advising teams on AI adoption strategy, running workshops, and collaborating to deliver a fully functional AI prototype that extracts and analyses performance signals from public documents at scale• Partnering with government agencies to rapidly extract insights from large‑scale textual datasets (public consultations, surveys, internal and external policy documents) under tight deadlines• Designing custom AI analysis workflows tailored to sector‑specific challenges across justice reform, climate policy, and urban planning initiatives• Translating non‑technical stakeholder requirements into production‑ready AI solutions ‑ conducting needs assessments with domain experts developing evaluation‑criteria‑driven prompts• Building pipelines that combine theme extraction, sentiment analysis, and automated statistical reporting item• Deliver end‑to‑end solutions from workflow architecture, to implementation, to automated report generation, enabling clients to process months of manual analysis work in days while maintaining analytical rigor and policy relevance• Synthesize complex AI‑generated insights into actionable policy recommendations through co‑authored reports and stakeholder presentations, translating technical findings into narratives that resonate with government decision‑makers and non‑technical audiences• Tools used: Python, Azure OpenAI, OpenAI APIs, Langchain, GitHub
- The World Bank GroupData Scientistoctubre de 2023 - enero de 2026 (2 años y 3 meses)• Developing an AI‑powered diagnostic assistant for policy practitioners analyzing social sector challenges across 20+ developmental outcomes(maternal health, youth unemployment, education, etc.) using RAG‑based systems• Designed and implemented a multi‑modal query routing system that intelligently directs user queries between semantic search, statisticalanalysis, and visualization pipelines, improving response accuracy and reducing latency• Built comprehensive evaluation infrastructure using Langfuse for LLM observability, including annotation workflows, multi‑dimensional scoringsystems, and automated performance tracking across conversation quality, citation accuracy, and response relevance• Engineered context‑aware follow‑up question generation to guide users through structured policy diagnosis, reducing user drop‑off and im‑proving session depth by suggesting relevant next steps• Led product development for a 3‑person engineering team, coordinating backend (FastAPI/Python), frontend (React/TypeScript), and data sci‑ence workstreams while managing stakeholder feedback loops between knowledge base curation, UX research, and technical implementation• Tools used: Python, LLM APIs, Langfuse, GitHub, Weaviate (vector DB)
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Formación
- PhD in Economics & Innovation (Cum Laude)INGENIO ‑ Universitat Politecnica deValencia2023PHD iN ECONOMiCS AND INNOVATiON (CUM LAUDE)
- Masters of Science in Local Economic DevelopmentLondon School of Economics (LSE)2018MASTERS OF SCiENCE iN LOCAL