- Conducted feature engineering, spatial clustering, and population densitymodeling to evaluate SVV’s growth potential in the U.S., comparing GreenDropand SVV locations against demographic metrics and mapping expansionopportunities with geospatial data.- Developed a data-driven classification model for categorizing U.S. ZIP codes asurban, suburban and rural using geospatial analysis, hierarchical densitythresholds, and zips population density metrics within (CBSAs).

- Processed large-scale location data for 32K vessels to detect exportdisruptions at U.S. ports and Ukraine during the Russia-Ukraine conflict,clustering vessel movements and calculating dwell times near ports to quantifycongestion and supply delays.- Analyzed Sweetgreen's market saturation and expansion opportunities usinggeospatial clustering and income/population segmentation at the ZIP codelevel, creating a tool for research analysts to evaluate growth potential… Show more - Processed large-scale location data for 32K vessels to detect exportdisruptions at U.S. ports and Ukraine during the Russia-Ukraine conflict,clustering vessel movements and calculating dwell times near ports to quantifycongestion and supply delays.- Analyzed Sweetgreen's market saturation and expansion opportunities usinggeospatial clustering and income/population segmentation at the ZIP codelevel, creating a tool for research analysts to evaluate growth potential basedon income and demographic factors.- Built Python frameworks to automate calculations of financial indicators (e.g.,Terms of Trade, Risk Appetite Index). Developed ETL pipelines to integrate datafrom Haver, Bloomberg, and DataStream, ensuring quality checks andexternalizing insights through GS Marquee API. Show less