Full Stack Data Scientist & ML Engineer
Transforming data into actionable insights through advanced machine learning and statistical modeling
Hello! I'm Samuel Adetsi, a passionate Full Stack Data Scientist with a Master's degree from the University of British Columbia. I'm excited about building complete data solutions—from initial analysis and modeling to deploying interactive applications that make insights accessible to end users.
My academic and project experience spans the full data science pipeline: I've worked with high-performance systems, built ML pipelines on cloud platforms, and created web dashboards using modern frameworks. I'm particularly interested in A/B testing, statistical modeling, and developing recommendation systems that enhance user experiences across different industries.
What drives me is the challenge of translating complex data problems into practical solutions that people can actually use. Through my coursework and personal projects, I've learned to combine technical skills in Python, TensorFlow, and cloud technologies with web development tools like React and FastAPI to create end-to-end applications.
I'm eager to apply my full-stack data science skills in a professional setting, where I can contribute to building scalable ML systems that deliver real business value while continuing to grow and learn from experienced teams.
Download ResumeYears Experience
Projects Delivered
Technologies Mastered
ML Frameworks
Built an XGBoost model to predict ML training runtime with high accuracy. Deployed via FastAPI REST APIs and interactive Streamlit dashboard for real-time performance optimization.
Developed a PyTorch-based neural network for personalized health score predictions from user activity data. Features an interactive Dash dashboard for data visualization and insights.
AI-powered NLP system that extracts and scores resumes against job descriptions. Uses natural language processing to provide detailed feedback for resume optimization.
Developed a comprehensive Python package for automated exploratory data analysis (EDA). Streamlines the data analysis workflow with automated visualizations and statistical summaries.
Developed a comprehensive anomaly detection system for Industrial IoT using the MIMII dataset. Features real-time data simulation via ThingSpeak, machine learning-based anomaly detection, and time-series forecasting with an interactive dashboard.
CNN-based digit classification system using TensorFlow. Implements deep learning techniques for accurate recognition of handwritten digits with high precision.
I'm passionate about leveraging AI and data science to solve complex problems and drive innovation. Whether you're looking to optimize user experiences, build recommendation systems, or implement advanced analytics, I'd love to discuss how we can create impactful solutions together.