Hi, I'm Hammad Rizvi — B.Tech Computer Science & Design undergraduate ('28). Transforming complex datasets into clear, actionable business solutions and predictive models.
Rooted in algorithmic rigor, moving towards practical Machine Learning solutions.
I started my software journey writing low-level procedural logic in C and architecting object-oriented systems with Java. This algorithmic base allows me to understand computation beneath data libraries, rather than just treating machine learning as a black box.
Today, I leverage Python, Pandas, SQL, and Exploratory Data Analysis (EDA) to untangle real-world datasets, engineer descriptive features, and track production workflows via GitHub version control.
Tools and technologies I use to analyze and model data.
Real-world data case studies and analytical pipelines.
Granular data inspection and statistical profiling on academic records. Evaluated score disparities across socio-economic parameters and mapped key variance drivers.
Complex SQL query pipelines utilizing multi-table JOINs, subqueries, CTEs, and Window Functions (RANK, DENSE_RANK) to unlock revenue insights and churn metrics.
Supervised learning model leveraging Scikit-Learn (Random Forest / XGBoost) wrapped inside a live, interactive Streamlit deployment for real-time inference.
Interested in working together or hiring an intern who loves solving data problems? Drop me a line anytime!