I analyzed financial datasets with Python and Excel in the JPMorganChase&Co. Quantitative Research Virtual Experience, using quantitative analysis techniques to draw business insights and present findings.
I built a personal finance dashboard with Python, Pandas, Plotly, and Streamlit. It turns cleaned transaction data into income, expense, refund, and savings KPIs, with interactive charts and filters for exploring spending patterns.
For my customer shopping behavior project, I wrote SQL queries and built an interactive Power BI dashboard to explore purchasing behavior, payment preferences, revenue trends, and customer segments.
I’ve also analyzed restaurant and Netflix datasets, using data cleaning, exploratory analysis, and visualizations to surface trends. I’m actively building a data analytics portfolio on GitHub with documented EDA notebooks and data cleaning scripts.
