Cecilia Regueira
Economist and Data Scientist with over ten years of experience across higher education analytics, applied data science, and economic consulting. My work spans academic research and real‑world applications, with a strong focus on causal inference, statistical modeling, machine learning, and data visualization. I have led data‑driven projects for universities, international organizations, government agencies, and private firms, applying econometrics and advanced analytics to problems in pricing, public expenditure, labor markets, and decision‑making under uncertainty. I bring extensive experience translating complex analytical findings into clear, actionable insights for diverse stakeholders, and I am deeply committed to evidence‑based policy and data‑informed decision‑making.
Current Positions
Economist and Data Scientist with extensive experience in data analysis, applied statistics, machine learning, and data visualization.
I currently teach Statistics in the Master in Data Science at Universidad de Montevideo and work as a Senior Data Analyst in higher education analytics.
My work bridges academic research and applied data science, with a strong focus on pricing, public expenditure, and decision‑making under uncertainty.
📊 2022 – Present Senior Data Analyst Enrollment Research & Analytics – Iowa State University
Lead data modeling and analytics initiatives to support undergraduate and graduate recruitment and enrollment strategy Develop and implement innovative analytical models to improve student recruitment effectiveness Recognized with institutional awards for innovation in analytics and modeling
🎓📈 2023 – Present Professor – Statistics, Master in Data Science Universidad de Montevideo
Deliver graduate-level instruction in applied statistics for data science Teach probability, statistical inference, experimentation, and interpretation with a focus on machine learning applications
🎓📈2022 – Present Professor – Data Visualization, Master in Data Science Universidad de Montevideo
Lead courses on data visualization, emphasizing effective visual communication and data storytelling Train students in exploratory analysis and visualization to support data-driven decision-making
Research Interests
- Price dynamics and pricing strategies
- Applied econometrics
- Machine learning for economic data
- Public and financial data analysis
- Data visualization for decision‑making
🎓 Education
Master in Economics
Universidad de la República (Uruguay)
2017 – 2020
Thesis: Pricing Strategies of Supermarkets in Uruguay
Selected for publication in the department’s academic series
Postgraduate Degree in Big Data Analysis
Universidad ORT (Uruguay)
Certificate in Data Science & Analytics
Des Moines Area Community College (DMACC – USA)
- President’s List - Member of Phi Theta Kappa Honor Society
Bachelor of Science in Economics
Universidad de la República (Uruguay)
🎓📊 Selected Industry & Consulting Experience
With over a decade of experience applying data science and analytics across industry, government, and international organizations, my work includes:
-Senior Data Analyst — Iowa State University (Higher Education Analytics)
-Data Analyst — Corteva Agriscience (Agribusiness & Supply Chain Analytics)
-Analyst & Data Scientist — Consulting Projects in Uruguay & the United States
-External Consultant — Inter‑American Development Bank (IDB)
-Data Analyst — Ministry of Public Health, Uruguay
Experience spans academic research, government, consulting, and private sector, working with large‑scale datasets, ETL pipelines, and applied ML models.
📚 *Teaching, Thesis Supervision & Academic Activity**
Statistics – Master in Data Science, Universidad de Montevideo 📊 STATS
Data Visualization – Master in Data Science, Universidad de Montevideo 📊 NVD
Master’s Thesis Advisor
Advised graduate research on financial system regulation and market structure (2013–2023) Guided applied research on machine learning methods for price duration analysis
🧮 Applied Projects & Teaching Resources
This section highlights applied data science and visualization projects developed using publicly available U.S. datasets, designed both for teaching purposes and institutional analytics.
🏆 Honors & Awards
- Recruitment Innovation Award – Iowa State University (2024)
- Love DATAWEEK 2024 — First Place Award
- President’s List – DMACC
- Phi Theta Kappa International Honor Society
🧠 Technical Skills
Programming & Tools
R · Python · SQL · Stata · Power BI · Tableau · QlikView · Shiny
Methods
Regression · Machine Learning · XGBoost · Random Forest · Experimental Design · Data Visualization
Languages
Spanish · English · Portuguese
🌱 Beyond Work
📚 Current Reading (2026)
In 2026, my reading balances intellectual curiosity 🧠 with personal enjoyment 💫. On the analytical side, I am reading 📘 The Book of Why by Judea Pearl, which deepens my understanding of causality, causal reasoning, and counterfactual thinking 🔗, extending data science beyond prediction. I am also revisiting 📗 Thinking, Fast and Slow by Daniel Kahneman, a foundational work on judgment under uncertainty ⚖️ and cognitive bias, which continues to shape how I think about decision‑making in both research and applied analytics.
For emotionally heavier moments—when I’m drawn to stories that explore grief, vulnerability, and human resilience 💔➡️💪—I read the 📖 Boys of Tommen series. These novels are deeply emotional and introspective, offering space for reflection and emotional release rather than light escapism.
In addition, I am part of a 📘 book club, which provides a collaborative space for discussion and collective interpretation of a diverse range of texts.
Outside of reading, I enjoy 🧘️ yoga, a practice that helps me slow down, reset, and recenter 🌿. Beyond work, I deeply value 👨👩👧 time with my family—through shared activities, everyday conversations, or simply slowing down together—an essential counterweight ⚖️ to analytical work and a constant source of perspective ✨.