Chadian Data Scientist building ML solutions for public health and economic development in Sub-Saharan Africa.
Published researcher · M.Tech Data Science · Christ University, Bangalore
- 🌍 Chadian national focused on applying data science to real problems in Chad and the Lake Chad Basin
- 📄 Published at CSCT 2025 (NIT Sikkim) under Springer — ensemble ML for loan approval prediction
- 🧠 Building ML pipelines for public health, economic forecasting, and development analytics
- 📊 End-to-end experience: raw data → cleaned dataset → ML model → interactive Power BI dashboard
- 🤝 Open to collaboration with NGOs, research institutions, and development organizations
Languages & Data Python · Pandas · NumPy · SQL
Machine Learning Scikit-learn · XGBoost · LightGBM · CatBoost · SMOTE · Ensemble Methods
Visualization & BI Power BI · Matplotlib · Seaborn
Tools Jupyter · Git & GitHub · PySpark · NLP
ML pipeline predicting malnutrition risk in 9,826 Chadian children using DHS survey data. Gradient Boosting achieved 92% accuracy and 0.979 AUC. Key finding: 52.9% of Chadian children under five are malnourished. → View Project
Interactive dashboard built on 12 official INSEED government datasets — 98 indicators · 23 regions · 1993–2024. Health, Economy, Food Security & Demography. 🌐 Live Dashboard | → View Project
ML early warning system predicting bad harvest years for millet and sorghum using 43 years of FAO and NASA climate data. Key finding: rainfall alone cannot predict crop failure in Chad. → View Project
ML pipeline to predict Lower Respiratory Infection risk using DHS survey data from Chad — SMOTE balancing, 8+ models benchmarked, XGBoost/LightGBM best performers. → View Project
End-to-end BI + ML system integrating 7 World Bank datasets across 180+ countries. Decision Tree vs Random Forest benchmarking with 4-page interactive Power BI dashboard. → View Project
Peer-reviewed research benchmarking 10 ensemble algorithms. LightGBM achieved best accuracy (89%). Presented at CSCT 2025, NIT Sikkim, published under Springer. → View Project
Open to collaboration with development banks, NGOs, and research institutions working in Sub-Saharan Africa.