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I’m an early‑career data scientist trained in statistics, computation, and spatial analysis. I’m especially drawn to the development side of data science, like building tools, workflows, and visualizations that help people make sense of messy information.
Whether I’m wrangling thousands of biodiversity records or designing a reproducible geospatial workflow, my goal is always to make complex information clearer and more accessible. My projects showcase how I approach messy data, build reproducible workflows, and turn analysis into tools and visualizations that others can use. Explore what I’ve been working on in my projects page.
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About Me
Data scientist with a background in environmental science and experience working with complex, real-world data.
I work primarily in R and Python to build cleaner workflows and reduce the friction that comes with managing large datasets. I’m interested in roles where I can apply geospatial analysis and develop tools that make information easier to interpret and use in decision‑making.
Before moving into data science, I worked as a liaison between proposed development projects and environmental agencies, helping navigate regulatory requirements throughout the permitting process. That experience gave me a firsthand understanding of how technical information moves from analysis to real-world decisions. I’m interested in analytical roles where I can combine technical problem-solving with environmental domain knowledge to build tools and workflows that strengthen decision-making and organizational capacity.
Master of Environmental Data Science • University of California, Santa Barbara • 2026
B.S. in Environmental Science • University of Puerto Rico, Rio Piedras • 2023
Skills & Tools
Languages
R Python SQL
Geospatial
sf terra QGIS ArcGIS Pro
Data & Modeling
Monte Carlo simulation tidyverse pandas scikit-learn
Visualization
ggplot2 matplotlib Affinity
Workflows
reproducible workflows version control documentation
Applied
spatial analysis environmental data biodiversity data regulatory context
What I’m Working On Now
I’m currently expanding my data science portfolio through projects that combine statistical analysis, programming, visualization, and reproducible workflows. I’m particularly interested in building practical tools that turn messy datasets into information people can explore and use.