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About Me
Data Scientist & AI Engineer passionate about leveraging technology to solve real-world challenges, with a focus on Africa's unique opportunities.
Background
Aspiring Data Scientist and AI Engineer with a strong background in Mathematics and Information & Communication Technologies.
I design data-driven and intelligent solutions focused on real-world impact, particularly in healthcare, environmental, and agricultural challenges in Africa.
Driven by scientific rigor, curiosity, and resilience, I combine data analysis, programming, and machine learning to turn complex data into actionable insights and practical solutions.
A committed self-learner, I strongly believe in technology as a tool for human-centered and sustainable development.
What I Do
Building predictive models and intelligent systems that learn from data.
Transforming raw data into actionable insights through statistical analysis.
Creating technology solutions for real-world challenges in Africa.
Deploying and maintaining ML systems in production environments.
Tech Stack
Experience
Each role has been an opportunity to combine research, data science, and creativity to deliver impactful solutions.
Inov Services
Design and development of data-driven solutions for environmental intelligence (water quality, pollution, climate). Construction and optimization of backend systems with Django, Docker, and CI/CD pipelines. Research and experimentation with generative AI and machine learning. Technical supervision of interns.
LESCAL
Processing laboratory data sets and performing statistical analyses for scientific reports. Designing visualizations and validating analytical workflows.
Pehu Platform
Development of REST APIs and backend logic in C and JavaScript for a microservices architecture. Contribution to the internationalization of the platform and optimization of backend modules. Improvement of code reliability through TDD and modular design.
Education
Solid academic training that grounds my practice in scientific rigor and continuous learning.
Institute of Mathematics and Physical Sciences (IMSP)
Training in information technology with a focus on software development and computer systems.
Faculty of Science and Technology (FAST)
Rigorous training in pure mathematics: analysis, algebra, probability, statistics, and optimization.
“Data only matters when it improves real lives.”
Interested in working together?