Cecilia Regueira

NoteProfile

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.

Key words: data analysis, applied statistics, machine learning, and data visualization.

📄 Curriculum Vitae

View CV Online


Current Positions

👩🎓 July 2026 – Present

Volunteer Statistician

Statistics Without Borders

Provide pro bono statistical and data science support to nonprofit organizations and international development projects. Collaborate with multidisciplinary teams to apply statistical methods, data analysis, visualization, and evidence-based approaches to address social, health, education, and humanitarian challenges.

👩🎓 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

Previous Professional Experience

💻📊 2022 – July 2026

Senior Data Analyst

Enrollment Research & Analytics – Iowa State University

Although my formal title was Data Analyst, my role functioned as a lead data science position. I led institution-wide data modeling and advanced analytics initiatives that supported undergraduate and graduate recruitment and enrollment strategy, working closely with senior leadership and enrollment stakeholders. My work included designing and implementing innovative statistical and machine learning models, such as enrollment forecasting, recruitment targeting, and financial aid elasticity models, to improve student recruitment effectiveness and inform high-stakes decision-making. These efforts contributed directly to strategic planning, resource allocation, and institutional sustainability and were recognized with institutional awards for innovation in analytics and modeling.

Concluded this appointment in July 2026 following a relocation.


Research Interests

  • 📈 Price dynamics and pricing strategies
  • 📊 Applied econometrics
  • 🤖🧠 Machine learning
  • 💼 Financial data analysis
  • 🎯 Data visualization for decision‑making
  • 📚 Education
  • ️📑 Improving Policy

🎓 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 ✨.


📧 Contact
ceciliaregueira.m@gmail.com
LinkedIn · GitHub