Hired as a member of the research data team to analyze, visualize, and perform statistical and spatial analyses, in R, Sql, Psql, and Arcmap, on complex air pollution data sets from various cohorts of participants around the United States and manage and develop databases. Key projects include:Building a brand new national road network system for our database from OSM and Tigerline data to replace and remain consistent with the characteristics of the year 2000 national road network currently being used. Required manipulation of spatial objects in R as well as searching the internet for public road datasets.Constructing a new covariate to analyze participant addresses based on their distance from greenspaces to be used in air pollution research projects. Researched public green space datasets and built a national greenspace map using census data and spatial packages in R. Analyzing researchers’ collected air pollution data and research participant information to create air pollution predictions at various locations and times points as well creating usable and reproducible results from inconsistent and incomplete datasets.

Chosen from university wide applicants to participate in data science capstone projects and attend Introduction to Machine Learning in Python course. Key components included: Developing and completing a capstone group project with calCOFI, identifying locations of ocean acidification and hypoxia off the California coast. Creating an interactive map and other visualizations, using leaflet and Shiny in R, to develop a user-friendly way to navigate through and understand calCOFI's large datasets.Appointed as spatial data and environmental science expert for this project because of my geographic and environmental sciences background. Built the map and hypoxic identifiers on the map using spatial packages in R and diving deep into spatial analysis.

Assisted Crystal Bae in Data analysis in R and QGIS, cleaning data, creating plots, performing statistical and spatial analysis, and processing text to study the human perception of static and dynamic geo-visualizations. Key components included:Creating surveys using QGIS to create maps with varying characteristics to test human perception of visualizations.Analyzing results from surveys using language processing, spatial, and statistical analysis and building visualizations. Co-author of academic research paper to be submitted for publication, formatted in LaTeX.Attended weekly research meetings and discussions.

Researched state by state Drinking Water and Clean Water Assistance State Revolving Fund (SRF) programs Analyzed and curated data on State Revolving Funds (SRFs) Began research writings for a larger project by EPIC that will analyze how these SRFS work and who they benefit

Developed a personal research project analyzing WELL’s water education program, focusing on the water conservation efforts of three California regions Reviewed and curated California water news for the CEO’s use Assisted with communications and administrative projects Updated website using WordPress, DiviBuilder