Business Data Science
I design machine learning models, interactive dashboards, and automated pipelines that turn complex data into smart, scalable solutions—from predicting customer behavior to uncovering deep market insights.
From churn prediction and explainable ML to streamlined BI reporting, I connect data, tools, and teams so decisions are clear, defensible, and quick to act on.
Selected Work
Same work, sharper presentation—here are the projects I rely on to demonstrate analytics, BI, and ML in motion.
Streamlit + PyCaret AutoML with SHAP explainability and OpenAI recommendations. Upload customer data, train models, inspect churn drivers, and trigger retention strategies—all in one workflow.
A responsive personal portfolio designed to present academic background, skills, and data projects. Built with HTML/CSS and powered by GitHub Pages + Formspree for direct contact.
Combines real-time parking API data, weather, and congestion to forecast availability. ML models (Random Forest, XGBoost) feed interactive dashboards to cut search time and city congestion.
Built classification models on 2,000 phones with 21 features to predict price tiers. Highlights feature importance so teams can shape market positioning and product strategy.
A CNN trained from scratch to classify candlestick chart images and predict next-day stock direction. Tuned learning rates deliver stronger accuracy and faster convergence.
Capabilities
What I use most days to move from data collection to decisions.
Contact
Reach out for data analysis, BI, or ML collaborations. I respond within a day.