I built a Google Maps scraper for the Food & Drink Venue Survey in Mar del Plata, capturing venues across the city and assigning over 97% of them to 124 neighborhoods. I compared neighborhood density and ratings using a Bayesian score that accounts for review-count bias.
For Social Media Opinion Climate, I collected and analyzed 32,482 comments and 3,537 replies from Instagram posts. I validated a pretrained sentiment model against hand-labeled comments and adjusted estimates using a confusion matrix and bootstrapping.
At Socio-Urban Studies Group — UNMdP, I collect interview data and process it in Python and Excel for Power BI visualizations as part of a university-funded outreach project. My work includes fieldwork with neighborhood leaders and workshops on the right to the city.
I also processed Argentina’s EPH household survey microdata for a predictive model aimed at targeting labor formalization policies. In my administrative cashier role, I built automated spreadsheets to track income and expenses and designed an Excel sheet to prioritize outreach to low-activity customers.
