Maya Arnott

About Me

I am a current Master’s Student in Environmental Health Data Science at Columbia University, and graduated with a BA in Environmental Biology from Washington University in St. Louis. I am interested in data science, climate risk quantification, and applying spatial and statistical methods to environmental health and healthcare research.

Thesis (In Progress): Prostate Cancer & Environmental Chemical Exposures

My thesis investigates the associations between environmental chemical exposures and prostate cancer diagnosis and aggressiveness using high-dimensional epidemiological data. The analysis applies GWAS-style regression across 1000+ chemical exposure variables, with covariate adjustment for key demographic and clinical factors.

This project uses high-dimensional data analysis, regression modeling, principal component analysis, multiple testing correction, and mixture methods.

Key Skills

R - tidyverse, leaflet, sf, raster/terra, r5r, stats, MASS, caret, tidymodels, shiny
Python - pandas, numpy, statsmodels, scipy.stats, matplotlib, geopandas, pyearth, scikit-learn
SQL - querying and data extraction
Data Visualization & Interactive Dashboards - ggplot2, tmap, Plotly, shiny
GIS & Spatial Analysis - ArcGIS, QGIS, spatial data handling in R (sf, raster/terra) and Python (geopandas, rasterio)
Statistical & Predictive Modeling - regression, machine learning, MARS/Earth models, classification, clustering

Contact

Feel free to connect via LinkedIn, email me at marnott276@gmail.com, or explore my GitHub projects.