Gustavo Varela Alvarenga
Experience

Experience

Senior Data Science Researcher
Google
2025 — 2026
  • Designed a novel metric for evaluating content on the Search results page, enabling systematic assessment of content quality and pinpointing where relevant content was missing.
  • Assessed where Google’s AI Mode could benefit from AI agents, defining the cases in which agentic information retrieval would better fulfill user queries.
  • Evaluated the landscape of grounding and corroboration sources for AI Overviews, recommending higher-quality sources to validate AI-generated information.
Regional Head of Data Science, Latin America
Argus Media · São Paulo, Brazil
2021 — 2025
  • Founded and led the Latin American data science team, growing it to 12 data engineers and scientists across three departments, with a department head and team lead reporting directly.
  • Drove an 86% team-retention rate over nearly four years by building a culture of innovation and collaboration.
  • Spearheaded the creation and deployment of R-based data products and scalable R/Shiny applications on AWS, improving client decision-making and operational efficiency through automation.
  • Owned daily production of the two principal data science products, ensuring model integrity and accuracy of results prior to publication.
  • Instituted quality-assurance protocols and strict Git version control for the top revenue-generating product.
  • Partnered with business development and sales to design and present data science solutions to clients, increasing engagement and product adoption.
Lecturer
University of Maryland
2020 — 2021
  • Developed and taught a 400-level Computational Statistics course covering data wrangling, exploratory data analysis, and inferential modeling using SAS and SQL.
  • Designed data-backed research projects and evaluation strategies, guiding students through regression, logistic regression, and ANOVA.
NSF Mathematical Sciences Graduate Intern
Pacific Northwest National Laboratory (PNNL)
2019
  • Proposed and prototyped a PostgreSQL/MySQL RDBMS for a DOE/NETL/PNNL project, optimizing database architecture for processing efficiency.
  • Engineered a Python web crawler and a web application for experimental data input, improving data-collection accuracy.
  • Led an R programming workshop (blogdown, Shiny) for an all-women audience.
Lead Statistician
Agência Brasileira de Desenvolvimento Industrial (ABDI)
2013 — 2014
  • Evaluated the impact of public policies on Brazilian industrial development using simulation and quasi-experimental methods (difference-in-differences, propensity score matching), presenting findings to the Brazilian Minister of Industry.
  • Led collection and analysis of socioeconomic data informing policy recommendations; contributed to the web tool “The Competitiveness Decoder.”
Lecturer
Universidade de Brasília
2012 — 2014
  • Taught statistical modeling to undergraduates from non-STEM backgrounds, improving applied data-analysis skills through interdisciplinary, project-based methods.
Statistical Consultant
IPEA (Institute for Applied Economic Research)
2009 — 2013
  • Designed and executed studies using advanced statistical and econometric methods to evaluate Brazilian industrial policies, producing strategic recommendations.
  • Built data extraction and management pipelines, including web scraping for patent data and phonetic matching for dataset integration.
  • Advised senior researchers on statistical methodology across the research lifecycle.