Building data-driven systems that scale in emerging markets. Specialized in ML pipelines, predictive modeling, and deploying AI solutions that create measurable real-world impact.
- Currently engineering end-to-end ML pipelines for Agriculture & Recommendation systems
- Deepening expertise in MLOps — Docker, FastAPI, cloud serving on Azure
- Ask me about: predictive modeling, feature engineering, Python data stack, and IoT data analysis
- Based in Nairobi, Kenya — passionate about tech solving Africa's real problems
- Fun fact: Tabs > Spaces, and I will defend this in production
| Domain | Tools |
|---|---|
| ML / DL | TensorFlow, scikit-learn, Keras, XGBoost |
| Data | Python, Pandas, NumPy, SQL, MySQL |
| MLOps | Docker, FastAPI, Git, Azure, Linux |
| Databases | MongoDB, MySQL, PostgreSQL |
| IoT / Sensors | Time-series analysis, sensor data pipelines |
ML model predicting crop yield from soil, weather, and satellite features — enabling precision agriculture decisions
- Stack: Python, scikit-learn, FastAPI, Azure
- Outcome: Reduced input waste by ~20% in test deployment
- View Repo | Live Demo
Predicts churn risk for behavior and usage patterns, supporting retention strategy
- Stack: Python, XGBoost, Pandas, MySQL
- Outcome: Identified top 15% at-risk users with 82% recall
- View Repo
- LinkedIn: linkedin.com/in/samuel-gathogo
- Location: Nairobi, Kenya
- Open to: Data Scientist/ ML roles in agri-tech, fintech, Finance, and impact-driven organizations
