Profile Projects Publications Experience Contact
Economist · Data Scientist

Economics, econometrics, and the mathematics of uncertainty.

Working on econometrics, causal inference, and machine learning — currently at the United Nations.

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Profile

01 — About

Economist and data scientist, currently at the United Nations, applying econometric techniques and machine learning to large-scale data problems.

Independent researcher with publications in Q1 journals, specializing in Big Data applied to finance and public policy. I work with Python, R, MATLAB, and Stata to build models that combine econometric rigor with machine learning.

Founder of Caleta, a data analytics and business intelligence consultancy for institutional clients.

UN
Current institution
Q1
Indexed publication
Princeton
Macrofinance Summer School
4
Technical languages

Projects

02 — Technical work
Panel Data — Professional Earnings GitHub

Causal inference models using panel data in Python to analyze the determinants of professional earnings.

View repository →
UN Dashboards In production

Automated reporting and geospatial visualizations in ArcGIS Pro.

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Portfolio Intelligence & Due Diligence Coming soon

Quantitative fund screening, Sharpe/Alpha/Beta metrics, and executive investment reports. Service in development via Caleta.

View Caleta →
Algorithmic Trading Signals Coming soon

Systematic strategies with machine learning signals (XGBoost, LSTM) and rigorous backtesting. Service in development via Caleta.

View Caleta →
Risk Modeling & VaR Coming soon

Value at Risk, stress testing, and Monte Carlo simulations for portfolio risk management. Service in development via Caleta.

View Caleta →
Explore more on GitHub Profile

Notebooks and scripts covering econometric analysis, machine learning, and data automation.

github.com/michaelgonzalezv →

Publications

03 — Research
Q1 Journal — RIB&F
Actively Managed Equity Mutual Funds in Emerging Markets
Lead Author · DOI: 10.1016/j.ribaf.2024.102540

Working Papers

Research in Progress
Energy Uncertainty, Climate Anomalies, and Sovereign Credit Risk in Latin America
With José Astaiza (Universidad EAFIT). Quantile VAR and panel/SVAR analysis of how energy uncertainty and ENSO-driven climate anomalies transmit into sovereign CDS spreads across Mexico, Chile, Brazil, and Colombia. Coauthor profile: jogaasgo.netlify.app
Research in Progress
Dynamic Topic Modelling of Colombian Cryptocurrency Forums: Sentiment, Regulation, and Adoption Trends
Applying dynamic topic modelling (Blei & Lafferty, 2006) to Spanish-language cryptocurrency discussion forums to study how topic evolution and sentiment relate to regulatory announcements and adoption trends in Colombia. Methodology and preliminary results forthcoming.

Experience

04 — Track record
May 2026 — Jul 2026
Selected Participant
Princeton University — Macrofinance Summer School
  • Intensive training in macroeconomic modeling and financial frictions.
  • Selected among global applicants for this competitive program.
Aug 2025 — Present
Data Scientist & Quantitative Researcher
Caleta — Data Analytics & Consulting · Founder · Remote
  • Predictive models in Python and custom Power BI dashboards.
  • End-to-end project management: data engineering, statistical analysis, and decision support.
Jan 2022 — Dec 2026
Data Scientist
United Nations · Bogotá, Colombia
  • Automated critical reports and dashboards.
  • Trained AI models to resolve data inconsistencies at scale.
  • Built geospatial visualizations in ArcGIS Pro.
Aug 2020 — Dec 2021
Research and Monitoring Analyst
Universidad del Valle · Cali, Colombia
  • Causal inference models (panel data) in Python to analyze professional earnings.

Technical Stack

05 — Tools

Analysis & Modeling

PythonRStataMATLABPandasNumPy

Visualization & BI

Power BIDAXArcGIS ProMatplotlib

Data Science

Causal InferenceTime SeriesSQLETLSparkA/B Testing

In Progress

TensorFlowDeep LearningC++