Data Scientist · ML Engineer · Founder in the Making
I turn chaotic data into powerful intelligence. CS student on a mission to master Data Science, engineer production-grade ML systems — and eventually build a startup that makes AI accessible to everyone.
Tools I wield to extract intelligence from data, engineer scalable models, and build AI products.
From curious student to Data Scientist, ML Engineer, and one day — Startup Founder.
Each project reflects a step in my learning journey — from EDA to ML Engineering to AI Product Vision.
A thorough exploratory data analysis of global tech & data science salaries by role, country, and experience. Uncovered compensation trends using Pandas, Seaborn, and Plotly.
Built an XGBoost classification model to predict customer churn for a telecom dataset. Achieved 91% AUC-ROC with feature engineering, SHAP explainability, and hyperparameter tuning via Optuna.
Fine-tuned a DistilBERT model on Twitter data for 3-class sentiment analysis (positive, negative, neutral). Served as a REST API via FastAPI with Docker containerization and a live demo UI.
Startup concept: an AI-powered platform that gives small businesses access to predictive analytics, automated reporting, and actionable insights — no data scientists required. This entire site is the MVP.