Research Data Science Intern: Build Models & Pipelines

Universityofnotredame; Notre Dame (IN); On-site; USD 17,000 - 24,000; Part time

Job summary

University of Notre Dame is seeking a Research Data Science Intern to work with the Mendoza Research Team. You will support active faculty projects by cleaning data, building models, and creating clear visualizations.

You'll collaborate with full-time data scientists and gain hands-on experience in data pipelines and reproducible code. Ideal candidates are undergraduate students with Python or R skills, familiarity with data cleaning and basic statistics, and an interest in academic research.

Qualifications

• Currently enrolled undergraduate student in good academic standing.
• Coursework in statistics, econometrics, computer science, or analytics.
• Working proficiency in Python or R for data manipulation and analysis.

Responsibilities

• Data Engineering & Preparation: Clean, merge, and validate complex datasets including financial/market data, administrative records, survey results, and web-scraped data.
• Statistical Modeling: Assist in building, testing, and refining statistical and machine learning models.
• Code Optimization & Reproducibility: Write clean, reproducible code using Python and R; maintain documentation.
• Data Visualization: Create charts, plots, and summary tables to communicate findings.
• Documentation & Version Control: Maintain data dictionaries and organized code with Git workflows.
• Faculty Collaboration: Participate in team check-ins and discuss technical ideas with researchers.

Skills

Python

R

Data manipulation

Data visualization

Git/GitHub

SQL

Education

Undergraduate student in good standing

Coursework in statistics/econometrics/computer science/analytics

Tools

SAS

SQL

Git

Job description

University of Notre Dame is seeking a Research Data Science Intern to work with the Mendoza Research Team. You will support active faculty projects by cleaning data, building models, and creating clear visualizations.

You'll collaborate with full-time data scientists and gain hands-on experience in data pipelines and reproducible code. Ideal candidates are undergraduate students with Python or R skills, familiarity with data cleaning and basic statistics, and an interest in academic research.