Benjamin Umeh

At the United Nations World Food Programme, I build real-time tools for vulnerability analysis and food-security monitoring in Nigeria. I developed a Python Streamlit application that tracks WFP activity locations and provides detailed activity information.

I build RAG-enabled AI agents that query local vector databases and files through MCP, alongside neural-network early-warning models for insufficient food. I also design ETL pipelines, SQL Server data workflows, Tableau dashboards, and web applications for reporting and remote data-quality monitoring.

At mPharma Health, I built data transformations across Amazon Redshift, BigQuery, Snowflake, and Databricks, streamed real-time data with Kafka, and delivered analytics products in Superset and Metabase. I also built large-scale time-series forecasting and product-reallocation systems supporting thousands of products across hundreds of facilities.

My work spans AI engineering, data science, quantitative analysis, and business analytics—from local AI agents and FMCG executive dashboards to algorithmic trading strategies, statistical arbitrage, and portfolio optimization. I use Python, SQL, R, machine learning, statistical modelling, and data visualization to turn complex data into decisions.