All Projects

A collection of my work across data analytics, engineering, and product development.

Developed ETL workflows to process and validate CMS healthcare data, transforming raw datasets into structured fact and dimension tables for analysis.
Built SQL analyses and Tableau dashboards to evaluate hospital performance, uncovering insights on profitability, cost efficiency, and regional trends to support business decision-making.

SQLETLData WarehousingTableau

Processed and analyzed a 3M+ token dataset using Python and SQL, applying exploratory data analysis and model evaluation to improve response accuracy to 85%.
Developed end-to-end data and analytics pipelines for ingestion, inference tracking, monitoring, and optimization, reducing latency by 75% and infrastructure costs by 82%.

PythonSQLAzureAWS

Developed automated data analytics pipeline to collect, clean, validate, and process 1,000+ new internship postings daily, delivering insights to hundreds of students.
Applied automated classification models (GPT-4o, Google Gemini) to categorize job data and filter low-quality entries, increasing pipeline efficiency by 90%.

PythonSQLAWSData Pipelines

Analyzed 116,000+ global immunization records to identify patterns in vaccination coverage and support data-driven public health decisions.
Cleaned and transformed complex survey data, engineered features, and addressed class imbalance using SMOTE to improve detection of low-coverage regions.
Evaluated multiple models and identified XGBoost as top performer (F1-score: 96.7%, AUC: 0.99), generating insights to prioritize high-risk regions and optimize resource allocation.

PythonXGBoostscikit-learnSMOTEMachine Learning

Developed a skincare recommendation system using Python, TensorFlow, scikit-learn, and Streamlit to compare skincare products based on user preferences and skin concerns, with data sourced from Sephora through API integration.
Enhanced recommendation engine with data analysis and machine learning skills, ensuring seamless user interaction via Streamlit and robust data integrity with thorough preprocessing, handling 30% null values in different features.

PythonTensorFlowscikit-learnStreamlitAPI Integration

Integrated 10+ global datasets in Tableau to analyze AI and labor trends, identifying a 2,700% growth in generative AI investment.
Developed dashboards using calculated fields and trend analysis, revealing a 25% drop in worker confidence despite AI hiring expansion.
Evaluated automation risk across occupations, highlighting 48% exposure in routine jobs and uneven regional workforce impact.

TableauData VisualizationAnalyticsWorkforce Analytics