I am a Ph.D. candidate in Economics at UC Santa Cruz with a decade of professional experience in Argentina across the public and private sectors, consulting, and academia before moving to the United States in 2022. My work combines economics and data science to answer business and policy questions using both experimental and observational designs.
My experience in data science spans product measurement, experimentation, and forecasting. As a Data Scientist Intern at Netflix, I developed metrics to assess how advertising affects member experience. I validated these metrics through backtesting against historical experiments and used doubly robust machine-learning methods to estimate their causal effects on engagement outcomes relevant to revenue. At AGIP, the Buenos Aires tax authority, I developed short-term revenue forecasts using administrative tax data, combining time-series models with random forests and gradient boosting. My work covered data preparation, model development and validation, and diagnosing unexpected revenue movements to distinguish changes in underlying economic activity from data or institutional shocks.
Earlier in my career, I spent nearly four years at PwC, where I supported U.S. audit teams and progressed from associate to supervisor. I worked extensively with large ERP extracts and financial datasets, performing validation, reconciliation, exception analysis, and documentation under tight deadlines and review requirements. That experience gave me a strong foundation in data quality, analytical discipline, and producing work that needed to be transparent, reproducible, and reviewable.
I have also used causal inference with observational data to evaluate education and business-regulation policies. At the University of Buenos Aires, I used regression discontinuity designs and longitudinal administrative data to study how international mobility scholarships affected students’ academic progress, degree completion, and early labor-market outcomes. I supervised junior economists and presented findings to university leadership to inform program renewal and design. At Argentina’s Department of Production and Labor, I used administrative firm data and difference-in-differences designs to evaluate whether regulatory simplification and the digitization of business procedures reduced processing times and compliance costs, translating the findings into recommendations for implementation.
Through independent consulting projects, I have applied economic analysis to commercial and regulatory decisions. For CENCOSUD, I worked on the design and analysis of a randomized coupon experiment, using variance-reduction and customer-segmentation techniques to distinguish incremental spending from substitution across product categories and inform promotion targeting. In retail-expansion assessments involving CENCOSUD and Supermercados ECO, I combined household surveys with geospatial data to evaluate potential changes in shopping patterns, travel times, and access to food retailers. For SMATA, Argentina’s automotive workers’ union, I integrated production, sales, employment, and tax data to estimate demand responses and simulate how a proposed vehicle-purchase subsidy could affect sales, production, and employment under industry capacity constraints.