Say those three magical words: This Error Again
I'm a passionate Data Analyst with expertise in building end-to-end machine learning solutions and data-driven analytics pipelines. I specialize in transforming complex data into actionable insights through advanced SQL queries, Python programming, and statistical analysis. With hands-on experience in fraud detection systems, ETL pipeline development, and predictive modeling, I drive impactful business decisions using data science techniques.
- Programming Languages: Python, SQL
- Machine Learning: Scikit-learn, Classification, Regression, Model Evaluation (Precision-Recall, ROC-AUC), Imbalanced Data Handling, Feature Importance Analysis
- Databases & Query Languages: PostgreSQL, MySQL, SQLite, SQL optimization, Window Functions, CTEs
- Data Analysis & Manipulation: Pandas, NumPy, Jupyter Notebook, Excel (Advanced formulas, pivot tables)
- Data Visualization: Matplotlib, Seaborn, Power BI, Looker, Metabase
- Tools & Platforms: GitHub, Jupyter Notebook, VS Code, LeetCode, StrataScratch
- Specializations: ETL Pipeline Development, Exploratory Data Analysis (EDA), Data Cleaning & Preprocessing, Statistical Analysis, Feature Engineering
An end-to-end machine learning pipeline for real-time financial fraud detection. Leverages advanced feature engineering, ensemble models, and handles severely imbalanced datasets (0.13% fraud rate). Achieves 99.83% PR-AUC with automated ETL pipeline and production-ready fraud detection capabilities.
A complete data analytics project that analyzes vendor and inventory performance using SQL, Python, and Power BI to drive data-informed procurement and inventory decisions.