Education

The University of Chicago
M.A. COMPUTATIONAL SOCIAL SCIENCE, 2023

GPA: 4.0/4.0

Computational Social Science applies computational approaches in statistics and computer science to understand, model, and analyze the social world.

Honors & Awards:
The University of Notre Dame
B.A. POLITICAL SCIENCE, 2019
Minors in Economics & Italian Studies

GPA: 3.9/4.0

Study Abroad: John Cabot University, Rome, Italy 2018

Honors & Awards:
  • Phi Beta Kappa,
  • Magna cum Laude,
  • Departmental Honors in Social Sciences,
  • Dean's List all Semesters,
  • Pi Sigma Alpha (Political Science Honors)
    • Executive Board Secretary
  • Gamma Kappa Alpha (Italian Studies Honors)

Professional Experience

Data Scientist | Presidential Management Fellow

National Oceanic & Atmospheric Organization

Summer 2023 to Present

  • Implements innovative data models and natural language processing solutions of hiring and employee survey data in Python to optimize human resources operations, enhancing talent acquisition and employee retention and communicates findings to non-technical stakeholders to drive engagement
  • Designs, builds, and maintains four widely-used Tableau dashboards for use in monitoring employee attrition, diversity, annual survey, and workforce profile metrics across the organization using simultaneous SQL queries to validate static and dynamic data and producing advanced, interactive chart visualizations

Data Science Intern, Studio Data and Analytics

Warner Bros. Discovery

Summer 2022

  • Performed data manipulation and utilized machine learning approaches (Random Forest and xgBoost) in Python to model 3000+ HBOMax programs’ viewership trends using SQL relational databases in a cloud-based environment
  • Analyzed ticket sales and attendance trends for theatrical shows; built data visualizations in GGPlot, R-Shiny, and D3.JS and communicated findings to leadership to inform business decisions about extending show runs on Broadway

Teaching Assistant

The University of Chicago

Autumn 2022 to Spring 2023

  • Served as TA for the three core technical courses for the Master's program: Computer Science I, Computer Science II, and Big Data & High Performance Computing
  • Covered topics such as Python, SQL, Object-Oriented Programming (OOP), Relational Databases, Web Scraping, Decision Tree Architecture, Cloud Computing, Amazon Web Services (AWS), Flask, Apache Spark, Parallel Computing, Data Visualization, NumPy/Pandas, Machine Learning, & Predictive Modeling
  • Designed and led laboratory sessions, held private and group tutoring sessions, and supported in class and online instructional efforts

Legislative Data & Policy Analyst

Curriculum Associates

Fall 2020 to Fall 2021 (Full Time) | Fall 2021 to Summer 2023 (Half Time)

  • Conducted comprehensive research on educational legislation and political landscapes across all 50 states and presented findings, including insights into recent state and local elections, to regional vice presidents and senior leadership
  • Performed advanced query techniques to systematically retrieve, clean, and analyze legislative data, highlighting its implications for school districts and aligning with company priorities, ultimately contributing to an understanding of the educational landscape and potential strategies for improving student outcomes using company products

Product Manager (Digital Accessibility)

Curriculum Associates

Summer 2019 to Fall 2020

  • Interfaced with technical and non-technical staff about the development of Ed-Tech instructional materials that drive student success and engagement and make classrooms better places for teachers and students
  • Coordinated and oversaw the development and release of key digital accessibility feature sets (keyboard navigation, screen reader support, and closed captioning) by prioritizing the team's software engineering efforts

Intern

Office of United States Senator Amy Klobuchar

Summer 2023 to Present

  • Assisted with constituent services and the organization of various events, including researching the drafting of speeches, coordinating with participants and venues, and accompanying the Senator to provide on-site support

Projects

Data Visualization Portfolio

This data visualization portfolio aims to demonstrate how theoretical principles of effective visualizations can be applied to real-world scenarios. Additionally the projects exemplify how effective data visualization can enhance understanding and communication of complex information for different audiences.

  • Men’s Alcohol Consumption and Women’s Experiences of Intimate Partner Violence in Ukraine, 2007
    Visualization | Code
  • Global Access to Safe Drinking Water
    Visualization | Code
  • COVID-19 and Transportation: How the Pandemic Affected Where We Went and How We Got There
    Visualization | Code

Causal Inference with Machine Learning Python Tutorials

A set of Python tutorials applying machine learning techniques to causal inference estimation.

Much of causal inference literature and the associated code and packages are in the R language, so these tutorials intend to instruct Python users on how to use these approaches.

Women in Polictics and Misogynistic Twitter Mentions: Natural Language Processing Approaches

A natural language processing project analyzing tweets taregted at US Women Politicians from the week before the 2020 election. Uses topic modeling and regression to categorize and analyze misogyny in tweets.

Polititrack

PolitiTrack visualizes 2020 Presidential campaigning strategies by displaying the location and date of presidential candidate campaign events, along with relevant information about the audience and event type.

Technical

Proficiencies

Programming and Data Analysis
  • Python
  • R
  • SQL
  • Stata
  • Tableau
Machine Learning Tools
  • SciKit-Learn
  • Causal Inference with Machine Learning (CausalML, EconML)
  • Natural Language Processing (NLTK, SpaCy, GenSim)
  • Deep Learning (TensorFlow, PyTorch)
Web Development and Data Visualization:
  1. HTML/CSS
  2. Vue.js
  3. JavaScript
  4. D3.js
Cloud Computing and Big Data:
  1. Spark/PySpark
  2. AWS
  3. Snowflake