Education: BSc in Artificial Intelligence & Machine Learning, University of Limerick (Class of 2030) | Based in Tanzania
Portfolio: Visit My Live Portfolio
Certified: Google AI Professional, Google Data Analytics Professional, & DataCamp Python Data Associate

Passionate about Data Engineering, Generative AI, and Computer Vision. I build intelligent, cloud-native systems that solve real-world problems, with a strict focus on African infrastructure, fault-tolerant pipelines, and MLOps.

• Current Initiative: Scaling the Dar es Salaam Smart City Engine, a fully automated, cloud-native traffic telemetry pipeline.
• Continuous Learning: Deepening my expertise in deep learning frameworks (PyTorch) and Enterprise CI/CD.
• Open to Collaboration: I'm actively looking for open-source contributors for FaceLogTZ (offline-first CV attendance). Reach out or open a PR!

Languages & Core Architecture

Data Engineering & Cloud DevOps

AI, Machine Learning & MLOps

Dar es Salaam Smart City: Traffic & Weather Engine (Flagship)
Cloud-Native Data Engineering Pipeline & AI Dashboard
▹ Enterprise CI/CD & Ingestion: 100% autonomous serverless pipeline utilizing ThreadPoolExecutor for concurrent scraping and pytest for strict CI validation.
▹ Data Contracts & MLOps: Protects NoSQL schema drift with Pydantic and tracks model predictive drift (R² and MAE) via automated weekly retraining workflows.
▹ GenAI Integration: Utilizes Google Gemini 1.5 Flash to generate dynamic, live commute radio broadcasts.
🔗 View Repository | 🌐 Live Command Center

Enterprise Churn Interception
Machine Learning Model for Customer Retention
▹ Engineered predictive analytics to identify at-risk customers, enabling data-driven retention strategies.
▹ End-to-end ML pipeline from data processing to Streamlit deployment.
🔗 View Repository | 🌐 Live Demo

FaceLogTZ
Smart Attendance System powered by Computer Vision
▹ Offline-first architecture utilizing facial recognition deep learning encodings.
▹ Optimized specifically for low-light & real-world African environments.
🔗 View Repository

I am actively open to discussing Data Engineering roles, MLOps collaborations, or new infrastructure projects.