About Me:
I’m an Economics major with a specialization in Data Science, deeply passionate about using data to create meaningful change. With a strong background in data analysis, research, and machine learning, I focus on applying statistical insights to tackle complex issues. My goal is to drive improvements in both the public and environmental sectors, particularly in promoting renewable energy and sustainable practices. I’m committed to helping underprivileged communities by advocating for equitable access to public services and pushing for policies that advance social justice. Through my interdisciplinary approach, I strive to use data as a tool for progress and empowerment.
Work Experience
Schneider Electric Environmental, Health, and Safety Intern (Aug 2023-Present)
Schneider Electric, recognized as the most sustainable company in 2024, is a global leader in energy management and automation. As an intern in the Environmental, Health, and Safety department, I focus on data analysis to support workplace safety initiatives. I take raw data and transform it into actionable insights, helping to ensure a safe and sustainable environment for our team. My role combines my passion for sustainability with my skills in data analytics, allowing me to contribute meaningfully to Schneider Electric’s ongoing efforts to lead in sustainability and innovation.
Data Analytics | Public Policy | Environmental Sustainability | Social Equity | Research
A Blog
NYPD Hate Crimes
Exploring hate crimes in cities is crucial for community well-being and safety, especially in a diverse setting like New York City. Read more
Comparing Regression Techniques for Astronaut Mission Duration
As I delve into the data set, my focus is set on using the total number of missions as the dependent variable, with the other variables acting as predictors Read more
Research
Subway Lines and Social Divides: Analyzing Transit Disparities in NYC's Neighborhood
This study delves into the disparities in public transportation access across New York City’s neighborhoods, with a focus on subway transportation. Analyzing data from Manhattan, the Bronx, Brooklyn, Queens, and Staten Island, the research employs a decision tree algorithm to assess the interplay of various factors – borough, race, car-free percentages, commute times, and median household incomes (both owned and rented properties). This methodological approach enables a nuanced understanding of how these variables collectively influence public transportation inequalities. Our findings reveal significant gaps in subway accessibility, particularly affecting lower-income and minority communities. In response, the study promotes a restorative approach to address issues of transportation justice. This includes implementing a dual strategy: an inter-neighborhood approach to lessen disparities across different neighborhoods, and an intra-neighborhood plan focused on narrowing the gaps within individual neighborhoods themselves. These recommendations are aimed at promoting transportation equity and ensuring a more inclusive urban mobility framework. Read more