Job Description

The University of Notre Dame is more than a workplace! We are a vibrant, mission-driven community where every employee is valued and supported. Rooted in a tradition of excellence and inspired by our Catholic character, Notre Dame is committed to fostering an environment of care that nurtures the whole person—mind, body, and spirit. Here, you will find a deep sense of belonging, a culture that prioritizes well-being, and the opportunity to grow your career while being a force for good in the world. Whether contributing to world-class research, shaping the student experience, or supporting the University’s mission in other ways, you will be part of a dedicated team working to make a meaningful impact on campus and beyond. At Notre Dame, your work matters, and so do you!

About the Role The Mendoza Research Team provides the technical and quantitative backbone for faculty research across Accountancy, Finance, IT Analytics & Operations (ITAO), Marketing, and Management & Organization (MNO).

As a Research Data Science Intern, you will work directly alongside our team of full-time data scientists to support active, high-impact faculty research projects. This is a hands-on, highly collaborative role designed to offer direct mentorship, build your applied technical toolkit, and give you real-world experience in data pipelines and statistical modeling.

Key Responsibilities

• Data Engineering & Preparation: Clean, merge, and validate complex research 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 standard data science languages (primarily Python and R).
• Data Visualization: Design intuitive charts, plots, and summary tables to communicate findings effectively.
• Documentation & Version Control: Maintain clear documentation, data dictionaries, and organized code repositories using Git workflows.
• Faculty Collaboration: Participate in team check-ins and contribute to technical discussions with faculty researchers.

What We Are Looking For:

• Currently enrolled Higher Education student in good academic standing.
• Proficiency in Python or R for data manipulation and analysis.
• Familiarity with data cleaning, basic statistical methods, and visualization tools.
• Strong attention to detail and an interest in academic or quantitative research.
• Experience with Git/GitHub, SQL, or web scraping is a plus, but not required.

Qualifications

Required:

• Currently enrolled undergraduate student, any major
• Coursework in statistics, econometrics, computer science, or analytics
• Working proficiency in Python or R
• Comfortable with (or eager to learn) tools like SAS, SQL, and Git
• Strong attention to detail and ability to follow data handling/confidentiality protocols
• Available for 15-20 hours/week

Preferred:

• Coursework in machine learning, causal inference, or experimental design
• Experience with large or messy real-world datasets
• Prior research assistant experience

How to Apply

Please submit:

1. A current resume/CV
2. A brief cover note (a few sentences on why you’re interested and any relevant coursework or projects)
3. An unofficial transcript
4. (Optional) A code sample or class project you’re proud of

Additional Information

• Compensation Starting at $15/hour
• Location On-campus
• Hours 15-20 hours/week during the academic term. We will work to structure your schedule around your academic requirements.
• Duration Starting Fall 2026

This position is accepting applications until September 2, 2026.

The University of Notre Dame seeks to attract, develop, and retain the highest quality faculty, staff and administration. The University is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, national or ethnic origin, sex, disability, veteran status, genetic information, or age in employment. Moreover, Notre Dame prohibits discrimination against veterans or disabled qualified individuals, and complies with 41 CFR 60-741.5(a) and 41 CFR 60-300.5(a). We strongly encourage applications from candidates attracted to a university with a Catholic identity.