About Me
I'm a passionate data scientist specializing in sustainability. I graduated in May 2026 my B.S. in Data Science at the University of Michigan and am pursuing an M.S. in Data Science at the Georgia Institute of Technology, expected Summer 2027. I want to combine data and machine learning with expertise in climate science to drive meaningful environmental impact and help companies reduce their carbon footprint.
My experience spans data science, machine learning, and sustainability analytics across various industries including tech, construction, and aviation. I'm particularly interested in leveraging AI and data science to solve complex environmental challenges.
Skills
Languages
Technologies
Frameworks
Experience
Data Science Intern
Meta
Built a sentiment proxy with Random Forest and Empirical Bayes for experiment monitoring, and engineered a classification pipeline processing 3B+ users daily.
Data Science Analyst
Delta Airlines
Built flight connection delay models (R² = 0.99) and a React/Flask inference tool, enabling 70% faster gate hold decisions at DTW.
Data Analyst Intern
University of Michigan - Office of Campus Sustainability
Designed Python Polars pipelines with TF-IDF and Gen-AI to classify Scope 3 emissions transactions, cutting manual labor by 60%.
Data Science Intern
Clear Estimates
Built GenAI-driven estimate generation and a distributed web scraper for RemodelingCosts.com, increasing leads 80% and cutting data collection time by 97%.
Featured Projects
MapReduce Simulator & Search Engine
Simulated distributed MapReduce system using TCP/UDP, fault tolerance, parallelization, and heartbeat tracking.