I’m a Data Analyst and M.S. Applied Data Science student at Clarkson University with experience in data analysis, machine learning, and data warehousing. I focus on building reliable data pipelines, applying machine learning to real-world problems, and translating data into actionable insights.

• Data analytics and visualization
• Machine learning and predictive modeling
• Data warehousing and ETL pipelines
• Data-driven decision-making for social impact

• Python (pandas, scikit-learn, matplotlib, seaborn)
• SQL (data modeling, star schema, SCD Type 2)
• Machine Learning (classification, class imbalance handling, model evaluation)
• Git & GitHub

• Wine Quality Prediction
  Binary classification of wine quality using physicochemical features, with logistic regression, decision trees, and random forest. Focus on class imbalance and model evaluation.

• ETL & Data Warehouse Pipeline
  End-to-end ETL and data warehouse implementation using star schema design and analytical reporting.

• Machine learning calibration and modeling on air sensor data, with a focus on improving prediction reliability.
• Pro bono data projects supporting organizations through data analysis, visualization, and reporting.

• Advanced machine learning techniques
• Analytics engineering and reproducible data workflows

Thanks for stopping by.