Professional Overview
Healthcare-focused data and AI professional with a biomedical engineering background. I build practical data systems using Python, Pandas, SQL, PostgreSQL, FastAPI, and Scikit-learn. Projects include a healthcare dashboard covering 10,483 facilities across 47 Kenyan counties, clinical workflow analytics, and AI-assisted maintenance triage.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built practical AI and data systems using Python, APIs and PostgreSQL
- Cleaned, structured, validated, and analysed datasets for software & AI workflow
- Developed backend workflows involving APIs, data processing and validation
- Used Git and GitHub for development, debugging, testing, and version control
- Documented technical implementations, testing results, and development decisions
Key Achievements / KPIs
- Built healthcare data projects covering 10,483 facilities across 47 counties
- Developed and deployed healthcare-focused data and AI applications.
- Implemented structured validation and error-handling workflows across projects
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built practical AI and data systems using Python, APIs and PostgreSQL
- Cleaned, structured, validated, and analysed datasets for software & AI workflow
- Developed backend workflows involving APIs, data processing and validation
- Used Git and GitHub for development, debugging, testing, and version control
- Documented technical implementations, testing results, and development decisions
Key Achievements / KPIs
- Built healthcare data projects covering 10,483 facilities across 47 counties
- Developed and deployed healthcare-focused data and AI applications.
- Implemented structured validation and error-handling workflows across projects
Education
Field of Study: Medical Engineering
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
