Bio
I’m a Chemical Engineer from Colombia transitioning into Data Science and Data Engineering. I combine a strong analytical and process-optimization background with hands-on skills in Python, SQL, Machine Learning, and data visualization to turn raw data into decisions.
My engineering training taught me to work with real-world, messy systems — mass balances, process variability, quality control — and that same rigor now drives how I approach data problems: understanding the pipeline end-to-end, from ingestion to a model or dashboard someone can actually use.
I’m currently building a portfolio of applied projects covering data pipelines, exploratory analysis, and machine learning models, documented and reproducible on GitHub. You can see them on the Portfolio page.
I studied Chemical Engineering at the Universidad Nacional de Colombia, and I’m based in Bogotá, Colombia, open to remote roles internationally.
What I work with
- Languages & Tools: Python, SQL, Git/GitHub
- Data Science: Machine Learning, EDA, statistical analysis
- Data Engineering: data pipelines, ETL, data cleaning at scale
- Visualization: Matplotlib, Seaborn, Plotly, dashboards
What I’m looking for
I’m actively seeking remote opportunities as a Data Scientist or Data Engineer, where I can apply my engineering background to solve real data problems with international teams.