Experience

View my Resume (PDF)

Awards & Honors

  • Stephen D. Durham Award (2022) — Awarded to the top senior statistics student for exceptional academic performance.
  • Phi Beta Kappa Honor Society (2022) — Top academic honor society in the liberal arts and sciences.
  • Palmetto Fellows Scholarship (2018–2022) — South Carolina state scholarship awarded for exemplary academic achievement.
  • Presidential Scholars Award (2018–2022) — South Carolina state scholarship awarded for high SAT/ACT scores.

Professional Experience

Data Analyst Intern

GreyNoise Intelligence — Finance and Operations Team

Jun 2023 – Sep 2023 | Washington, DC

  • Automated error checks, NAICS-to-industry classification, and vendor/transaction breakdowns in Excel, improving reporting efficiency.
  • Developed Excel models to streamline deal calculations, including mid-term upgrades and co-term merges.
  • Built a cash investment tracker integrating financial institution data to forecast monthly returns.
  • Analyzed customer churn and lead origins in R, identifying key drivers of churn and conversion.
  • Created an interactive Streamlit dashboard to visualize drivers and support retention strategies.

Undergraduate Research Assistant

Darla Moore School of Business — Division of Research

May 2021 – Oct 2021 | Columbia, SC

  • Reviewed literature on spatial segregation metrics and neighborhood effects in Charleston, SC.
  • Cleaned and analyzed MSA-level economic, social, and demographic data to study STEM worker agglomeration.
  • Calculated location quotients and ran regressions in Stata/R to identify drivers of STEM clustering across MSAs.
  • Redesigned course materials to meet university accessibility standards, improving usability for all students.

Undergraduate Research Assistant

University of South Carolina — Department of Economics

Jan 2020 – Jan 2021 | Columbia, SC

  • Digitized and organized CDC vital statistics data to support analysis of racial disparities in birth outcomes post-hospital desegregation.

Technical Skills

  • Languages & Databases: R, Python, SQL; Familiar with Java, Stata, SAS
  • Libraries & Frameworks: tidyverse, NumPy, pandas, matplotlib, PyTorch, TensorFlow, Streamlit, Hugging Face Transformers; Familiar with PySpark
  • Developer Tools: Git, Jupyter Notebook, Google Colab, Markdown, LaTeX
  • Software & Tools: Microsoft Office Suite (Excel, Word, PowerPoint), Figma
  • Data Science & Machine Learning: Statistical analysis, hypothesis testing, A/B testing, forecasting, predictive modeling; Supervised learning (linear/logistic regression, decision trees, random forests, KNN, SVM); Unsupervised learning (clustering, dimensionality reduction); Neural networks, NLP