ML Engineer & Data Scientist
Building data-driven systems and AI products for real users. Focused on recommendation systems, computer vision, and scalable ML solutions.
I am a self-taught Machine Learning and Software Engineer with over 3 years of hands-on programming experience, focused on building data-driven systems, ML models, and practical AI applications.
My background spans Python, AI/ML, backend development, and data science, with strong foundations in statistics, probability, and linear algebra. I approach problems systematically—breaking them down, reasoning through edge cases, and prioritizing correctness, clarity, and scalability over shortcuts.
I have experience working both independently and in collaborative environments, including serving as a developer team lead across projects and competitive hackathons. My technical interests include recommendation systems, applied machine learning, computer vision, NLP, and AI products built for real users, not just academic demonstrations.
My long-term goal is to build and scale AI-powered products and startups, particularly solutions tailored to local and emerging markets.
Designed a mentee-first recommendation system using ML ranking models to predict successful mentorship outcomes. Integrated PostgreSQL directly into the ML pipeline with explainable recommendations and automated retraining capabilities.
Built an MVP system to diagnose crop diseases from images using computer vision. Applied preprocessing, feature extraction, and classification while addressing real-world challenges like noisy images and limited datasets.
Developed a comprehensive school management system for handling student records, staff data, and administrative workflows. Designed relational database schemas and implemented full CRUD functionality.
Built predictive models using historical market data with focus on modeling patterns and uncertainty. Performed comprehensive feature engineering, data preprocessing, and evaluation while avoiding overfitting.
Developed regression models to predict property prices using features like location, distance metrics, and property age. Implemented end-to-end ML workflow from preprocessing to evaluation.
Built a text classification model to identify spam emails using NLP preprocessing and feature extraction. Reinforced understanding of text-based ML pipelines and model evaluation techniques.
Led a development team on an applied machine learning project focused on real-world problem solving. Coordinated technical decisions, model development, and implementation workflows. Worked with data preprocessing, feature engineering, and model evaluation while gaining experience in teamwork, leadership, and responsible AI considerations.
Led ideation, system design, and technical implementation of an AI-based solution. Coordinated team tasks under strict time constraints and presented the solution to judges, gaining experience in technical communication and rapid problem-solving.
Managed task allocation, technical direction, and collaboration across international team members. Strengthened leadership, rapid problem-solving, and cross-functional teamwork skills while working under pressure.
Mentored beginners entering programming and machine learning, providing guidance on Python fundamentals, problem-solving techniques, and learning paths. Taught Python fundamentals using hands-on approaches, covering core topics and emphasizing practical implementation. Focused on building strong technical thinking and confidence.
Focus on supervised learning, model evaluation, and practical ML workflows
Covered networking basics, security principles, and threat awareness
Introduction to cybersecurity roles, tools, and foundational practices
Completed a structured program covering Python programming and applied machine learning
Gained foundational understanding of blockchain concepts and applications
I'm always interested in hearing about new projects and opportunities. Based in Zamfara State, Nigeria.