
I am an Economist but I work as a Quantitative Analyst and Data Scientist passionate about bridging econometric modeling, data engineering, and experimentation to address real-world challenges. My work involves building APIs and software solutions that automate mathematical models, applying advanced techniques like stochastic calculus and time series analysis.I aim to become an applied-experimental economist, leveraging data and computational tools to better understand human behavior and improve decision-making processes. By combining theory with hands-on experimentation, I seek to develop impactful, data-driven solutions.
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I gave assistance to 4 undergraduate courses for the UNA-School of Economics where I created more than 20 Notebooks in R and Python with almost 10 hours of video lessons for the students interested in programming languages. I was an assistant for the professor Msc Alexander Amoretti Alvarado.
• Microeconomics I, ECF404
• Econometrics I, II, III, ECF411, ECF412, ECF413
I did research in the field of computational economics for the Tax Issues Project of the School of Economics of the Universidad Nacional de Costa Rica, supervised by the Msc David Ricardo Cardoza, using linear programming to create computable general equilibrium models.
I conducted surveys on illicit credit practices, building trust with participants to gather sensitive data, and accurately entered responses into digital systems.
I ensured data quality through validation and maintained strict confidentiality throughout the process.
During my time as a Data Scientist for Joystick FIFCO I used high level solutions for Marketing purposes such as categorize unified individuals using the Customer Data Platform of FIFCO with more than a 1000000 unified profiles for 8 countrys.
I Structure and create Machine Learning models and Deployed them using Cloud Computing tools like VertexAI, CloudRun and BigQuery. I worked with more than 10 brands like Pilsen, Imperial, Heineken, Gatorade and Bavaria.
Developed and implemented econometric-statistical models to simulate financial stress scenarios using techniques like multivariate regression, time series analysis, and Monte Carlo simulations. Leveraged advanced mathematical techniques, such as linear algebra and stochastic calculus, to model the impact of extreme market conditions on portfolios and financial institutions. Created APIs to enable software solutions that automate mathematical models, integrating Data Engineering tools like Plumber. Collaborated with risk managers, mathematicians, and statisticians to ensure accurate model implementation and effective result interpretation. Prepared detailed reports and presented stress-testing findings to senior management in a clear, accessible manner. Contributed as a Quantitative Analysis specialist for Financial Services and Risk Management.
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