Christopher Hynes

Experience / Education / Capabilities

Experience &
education.

Experience across academic research, business analytics,
and graduate computer science.

Download my résumé

Research & industry

Jun–Sep 2023

Data Analyst Intern

GreyNoise Intelligence

Finance & Operations · Washington, DC

  • Analyzed customer churn and lead origins in R to investigate drivers of retention and conversion.
  • Automated data-quality checks, NAICS classification, and vendor/transaction reporting in Excel.
  • Built models for contract changes and an investment tracker to forecast monthly returns.
  • Created an interactive Streamlit dashboard to communicate churn and conversion analysis.
Related project: customer-retention analysis
May–Oct 2021

Undergraduate Research Assistant

Darla Moore School of Business

Division of Research · University of South Carolina

  • Cleaned and analyzed MSA-level economic, social, and demographic data to study STEM-worker agglomeration.
  • Calculated location quotients and ran regressions in Stata and R to examine geographic clustering.
  • Reviewed literature on spatial segregation and neighborhood effects; adapted course materials for accessibility.
Jan 2020–Jan 2021

Undergraduate Research Assistant

University of South Carolina

Department of Economics

  • Digitized and organized CDC vital statistics data to support research into racial disparities in birth outcomes following hospital desegregation.

Education

2024–2026
Expected Dec. 2026

Georgia Institute of Technology

M.S. Computer Science · GPA 4.0

Graduate work in machine learning, health informatics, NLP, robotics, algorithms, and human–computer interaction. Four ML studies covered supervised and unsupervised learning, randomized optimization, and reinforcement learning on datasets with up to 7.7 million records.

2018–2022

University of South Carolina

B.S. Statistics & Economics · Honors College

Summa cum laude · GPA 4.0. Honors thesis applying synthetic control to Chile’s economic reforms. Coursework included econometrics, labor economics, development economics, and urban economics. Study abroad at Universidad Carlos III de Madrid, 2021–2022.

Technical skills

Methods, languages, and tools.

Research & evaluation

Statistical inference, causal inference, synthetic control, experimental comparison, robustness checks, repeated trials, model selection, and quantitative user research.

Data & machine learning

Python, R, SQL, PyTorch, scikit-learn, TensorFlow, Hugging Face Transformers, pandas, NumPy, and tidyverse. NLP, predictive modeling, and reinforcement learning.

Additional familiarity: Java, Stata, SAS, and PySpark.

Systems & communication

FastAPI, asyncio, Docker, Linux, Git, GitHub Actions, Streamlit, Excel, Figma, technical reports, and data visualization.

Selected honors

Stephen D. Durham AwardTop senior statistics student · 2022

Phi Beta Kappa2022

Palmetto Fellows & Presidential Scholars2018–2022