About me
I’m a Data Scientist and Ph.D. graduate in Statistics from Rice University under the direction of Dr. Marina Vannucci. My work focuses on Bayesian modeling for multivariate and count data, with applications in healthcare, sports, and social science. I’m currently interning at Amazon, developing deep learning models to analyze community sentiment from diverse data sources.
When I am not immersed in data and research, I love soccer –watching or playing– as well as exploring new places and taking pictures. Check out some of my travel photos here.
Research Interests
- Bayesian Modeling
- Machine Learning
- Statistical Computing
- Graphical Models
- Applied Statistics
My latest projects involve developing frameworks for estimating graphical models that identify relationships or dependencies between different mixed data types.
A list of projects can be found here.
Education
I completed my undergraduate studies in Bogotá, Colombia, earning a BS in Mathematics from Universidad Sergio Arboleda with a tuition waiver scholarship. I also hold a BS in Statistics from Universidad Nacional de Colombia, where I graduated first in my class. I recently completed a PhD in Statistics at Rice University, where my research focused on Bayesian modeling for complex multivariate and count data.
Selected Experience
Data Scientist Intern, Summer 2025
AmazonData Scientist, 2019 - 2020
MincienciasData Analyst, 2017 - 2018
Universidad del RosarioLecturer
See the full list of courses here.
MOOCs
- Deep Learning. (DataCamp, 2024) [Certificate]
- Developing LLM. (DataCamp, 2024) [Certificate]
- R Developer. (DataCamp, 2024) [Certificate]
- Applied Data Science with Python Specialization - University of Michigan (Coursera, 2019) [Certificate]