A b o u t M e

Ready to transform data into actionable insights, I am a forward-thinking, highly motivated young woman currently pursuing an M.S. in Data Science at the University of Virginia. My journey, starting with a B.A. in Economics, honed my analytical insight and curiosity through rigorous research and exploration. These academical pursuits have equipped me with a unique blend of skills, combining strategic thinking fostered by my economics background with technical expertise gained from data science.

I thrive on challenges and approach problem-solving with a tenacious work ethic, consistently seeking innovative solutions. When working with others, my bubbly personality and collaborative spirit make me a valuable team player. I bring energy and enthusiasm to every project, fostering a positive work environment.

In my personal time, I love exploring new places and cultures, valuing experiences that broaden my perspective. Whether cheering for my favorite sports teams (Wahoowa!), engaging in activities to stay active, or immersing myself in insightful podcasts and books, I bring the same passion and dedication to my personal pursuits as I do to my educational and professional endeavors.

Let's connect!

S k i l l s

  • Python
  • R
  • HTML
  • CSS
  • SQL
  • MongoDB
  • GitHub
  • Tableau
  • Microsoft Excel

E x p e r i e n c e

The skills I have gained inside the classroom have allowed me to further practice and advance my skills outside of the classroom, both in extracurricular and professional settings, all of which I hope to bring into my future career.

Resumé

P o r t f o l i o

Here's a compilation of my favorite data science coursework and personal projects that I have completed throughout the years from newest to oldest:

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Continuous Glucose Monitoring

TEAMWORK ● PROJECT MANAGEMENT ● MISSING DATA IMPUTATION ● TIME SERIES ANALYSIS

In Progress: Sept 2023 - Present
Collaborating in a four-person team looking to advance our understanding of CGM data analysis, with a focus on the implications of missing data and the potential to derive meaningful insights in the presence of such data challenges. Additionally, we aim to determine an effective way to impute the missing data.

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Modeling Injuries in Competitive Runners

TEAMWORK ● DATA CLEANING ● PYTHON ● BAYESIAN MACHINE LEARNING ● MODELING ● VARIATIONAL INFERENCE

Nov - Dec 2023
Collaborated in a three-person team focusing on modeling and understanding injuries in competitive runners using Bayesian Machine Learning techniques including a Beta-Binomial Model with HMC Sampling and ADVI Approximation.

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King County, WA Housing Market

TEAMWORK ● R ● DATA ANALYSIS ● STATISTICAL MODELING

Jul 2023
Collaborated in a four-person team with a focus on analyzing and predicting trends in the King County, WA housing market based on 21,614 houses sold. Employed statistical modeling techniques, particularly linear and logistic regression, to explore the impact of various house attributes on selling prices and the likelihood of a property being situated in one of the region's "20 Wealthiest Zip Codes."

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Diamond Pricing Analysis

TEAMWORK ● R ● DATA ANALYSIS ● LINEAR REGRESSION

Jul 2023
Collaborated in a four-person team to conduct an analysis of over 1,000 diamonds from Blue Nile, examining the impact of factors like cut, clarity, color, and carat on diamond prices. Findings validated and disproved various claims made by Blue Nile, supporting the conclusion that the positive relationship between price and carat is a key determinant in diamond pricing.

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Celebrity Facial Recognition

TEAMWORK ● WEB SCRAPING ● FEATURE ENGINEERING ● WEB CRAWLING ● PYTHON ● IMAGE CLASSIFICATION ● CNN ● HTML ● CSS

Jan 2023
Collaborated in a three-person team to web scrape and crawl hundreds of images of diverse groups of celebrities. Passed these images through a convolutional neural network (CNN) to train and validate and eventually identify celebrities with high accuracy.

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Drinking Water Quality

TEAMWORK ● DATA CLEANING ● R ● SHINY ● GGPLOT ● DATA VISUALIZATION ● DATA ANALYSIS ● MACHINE LEARNING ● HTML ● CSS

Jan 2023
Collaborated in a three-person team to develop a Shiny app visualizing and analyzing water quality metrics, as well as train Random Forest and Decision Tree Models to predict non-potable water.

See more Shiny App GITHUB 

ROI of College Football

DATA COLLECTION ● DATA CLEANING ● MULTIPLE LINEAR REGRESSION ● DATA ANALYSIS ● TABLEAU ● EXCEL

Oct - Dec 2022
Collected college football financial and standing data to create my own regression in order to determine how a program's revenues and expenses can affect its standing and performance.

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Analysis of Bad Drivers

TEAMWORK ● R ● GGPLOT ● SHINY ● DATA COLLECTION ● DATA VISUALIZATION

Nov - Dec 2022
Collaborated in a three-person team to analyze fatal collisions in the continental United States and discovered how geography can play a large role through various visualizations.

GITHUB 

HOLIDAY ETL DATA PROCESSOR

API CALL ● DATA TRANSFORMATION ● SQL DATABASE

Oct 2022
Created a segment of an ETL pipeline that ingests and processes raw data extracted from a holiday API, transforms it, and inserts it into a SQL database.

GITHUB 

NETFLIX CHATBOT

PYTHON ● DATA TRANSFORMATION ● MONGODB ● CHATBOT

Oct 2022
Used data on Netflix TV shows and movies to create an ETL pipeline to extract, transform, and load multiple datasets from CSV files into a MongoDB database to then create a chatbot.

GITHUB 

Analysis of Student Exam Performance

TEAMWORK ● PYTHON ● TABLEAU ● DATA COLLECTION ● DATA VISUALIZATION ● DATA ANALYSIS

Jun 2021
Collaborated in a two-person team to analyze how different factors (gender, race, socioeconomic status, etc.) can affect math, reading, and writing test scores. Tableau visualizations were created to present findings.

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DATABASES: DISCUSSSING POPULAR ARCHITECTURES

TEAMWORK ● DATABASES ● MYSQL ● MONGODB ● NEO4J ● PYTHON

Jun 2021
Collaborated in a four-person team to design a custom dataset, populate it into MySQL, MongoDB, and Neo4j, write Python scripts to query each of them, and examine the strengths and weaknesses of each database architecture.

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Guide to finding the right college

TABLEAU ● PYTHON ● DATA COLLECTION ● DATA VISUALIZATION ● DATA ANALYSIS

Jun 2021
Presented a guide for students to find the right college with attention towards diversity, tuition cost, and post-grad salary. Tableau visualizations were created to present findings.

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Analysis of Global Economic Freedom

PYTHON ● DATA COLLECTION ● DATA CLEANING ● DATA VISUALIZATION ● DATA ANALYSIS ● PLOTLY

Sept 2020
Analyzed global economic freedom based on gap between the most and least economically free countries and regions and created a scatterplot and map visualization to show findings.

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2019 NCAA COLLEGE BASKETBALL

PYTHON ● DATA COLLECTION ● DATA CLEANING ● DATA VISUALIZATION

Feb 2020
My first ever data science project: Analyzed the power ratings and postseason results of the 2019 NCAA College Basketball season to determine whether overall power rating affects postseason success.

GITHUB