🐦 Twitter/X: @Andredex_data

📍Based: San Francisco Bay Area

Hello! I'm Andre, a recent Environmental Data Science graduate from UC Santa Barbara. I worked as a Research Assistant at the Jasechko Research Lab, where I developed my expertise in climate research, particularly in waterway resilience in the Jack & Lautra Dangermond Preserve. My significant achievement includes leading a Master’s Capstone Project with The Nature Conservancy (TNC), where my team and I conducted a vital study on the impact of wildfires on California's groundwater-dependent ecosystems (GDEs) using geospatial analysis tools in R. I have also engaged deeply with USGS water data, creating interactive maps and visualizations to better understand and communicate water usage patterns. My work is driven by a deep commitment to environmental sustainability and a passion for unlocking insights through data analysis. I am particularly interested in water data analysis, striving to integrate my technical skills in data science to influence and improve water policy and management in California. I am always keen to collaborate on projects that use data to drive environmental sustainability and enact meaningful policy transformations.

💻📊 Currently, I'm expanding my skill set with online classes in JavaScript, R-Shiny Dashboards, and AI via Udemy. My goal is to enhance my ability to transform complex data into clear, actionable insights and solutions, specifically focusing on water resources. This involves applying these advanced skills to address real-world challenges in water management and conservation.

• May 16 - May 18 2023: Data Analysis and Visualization in Python Workshop (Cleaned & Created Visualizations in Python)
• Fall 2022: Environmental Data (Used Python and Google Earth Engine for environmental data analysis)
• Summer 2022: Python for Environmental Data Science (Introduction to Python)

• Spring 2023: Text Sentiment Analysis (Used R for text processing, classification, semantics, and natural language parsing)
• Spring 2023: Modeling Environmental Systems (Used R to develop static, dynamic and spatial models)
• Winter 2022: Environmental Policy Evaluation (Used R to measure the causal effect of policies on environmental outcomes of interest)
• Winter 2022: Machine Learning (Used R to automate and process big/complex data to extract knowledge)
• Fall 2022: Statistics for Environmental Data Science (Used R to determine if there is a statistically significant relationship between groundwater levels and fire size in California)
• Summer 2022: Introduction to R masters course (Learned basics of R and GitHub)
• Winter 2021: Exploring Water Data (Big Data Wrangling & Visualization in R)
• Summer 2020: Geographic Information Systems Introduction (GIS applications in R)

• MEDS (2022): Master of Environmental Data Science (Bren School of Environmental Science & Management - UC Santa Barbara)
• BA (2021): Environmental Studies (UC Santa Barbara)

💧🔥 Master’s Capstone Project: Led an interdisciplinary team in geo-spatial analysis using R and GIS to assess the interaction between California's groundwater-dependent ecosystems and wildfires, creating an R-Shiny dashboard for data exploration and engaging with stakeholders at The Nature Conservancy.
💧📡 Research Assistant, Jasechko Research Lab: Collaborated on climate adaptation research focusing on waterway resilience, processed and analyzed water samples, transformed extensive data into ArcGIS shapefiles, and improved field data collection efficiency and integrity at the Dangermond Preserve.
💧💻 Water Data Research Project: Conducted a detailed analysis of historical USGS water data using R, created visualizations to illustrate water withdrawals by sector and source, and developed an interactive map to explore water usage across the U.S. states.