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Summary

Job Description

The Mendoza College of Business seeks a Research Data Scientist to serve as the primary technical research support professional for the Mendoza Behavioral Lab (MBL) and will also support other faculty research initiatives. This role bridges IT infrastructure, behavioral experimentation, and research technology, enabling faculty and research teams to design, execute, and analyze high-quality experimental studies efficiently, securely, and reproducibly.

The Research Data Scientist partners closely with Mendoza faculty, Mendoza IT and Central IT to support experimental workflows, maintain lab technology, and develop robust data pipelines across a wide range of behavioral and business research projects.

Key Responsibilities

Provide hands-on technical and IT support for behavioral experiments, including real-time troubleshooting to ensure smooth study execution and data integrity.
Consult with faculty to design, develop, and maintain reproducible data workflows using R, Python, and SQL to build software for experiments and applied research projects.
Integrate and manage data from multiple sources (e.g., surveys, biometric tools, experimental platforms, VR systems) into clean, analysis-ready datasets.
Develop and document data pipelines, scripts, and data dictionaries to support replication, long-term data management, and research continuity.
Collaborate with MBL program director and research teams to ensure the study design adheres to IRB requirements and campus security standards.
Partner with Mendoza IT, Central IT, and the Center for Research Computing to ensure compliance with university policies and best practices.
Stay current with emerging research technologies and data science tools through professional development, training, and conferences.

Qualifications

Required Qualifications

Bachelor’s degree in Data Science, Computer Science, Information Systems, or a related field.
At least 1–2 years of experience in data science, research computing, or applied data workflows.
Proficiency in R and/or Python and SQL for data manipulation, integration, and analysis.
Experience with Amazon Web Services and Google Cloud Platforms
Experience managing and integrating datasets from multiple research or enterprise sources.
Strong analytical, problem-solving, and workflow design skills.
Excellent communication, consulting and documentation skills, with the ability to collaborate across technical and non-technical teams.
Commitment to data integrity, security, and compliance in human-subject research environments.

Preferred Qualifications

Master’s degree in Data Science, Computer Science, or a related field.
Experience working in academic research labs or behavioral research settings.
Familiarity with tools such as iMotions, Qualtrics (including JavaScript customization), and VR platforms.
Experience integrating behavioral and biometric data with enterprise or large-scale datasets.
Knowledge of Windows systems administration and enterprise tools (e.g., Active Directory, SCCM, Intune, Group Policy).
Demonstrated ability to support complex, multi-study research environments.

Additional Information

Application Deadline to Apply (subject to change): Sunday, 2/22/26
Please note this is a full-time (40 hours per week) position that is fully onsite, based within the Mendoza College of Business, supporting the Mendoza Behavioral Lab.
Salary commensurate with experience
Please include a cover letter in your application for full consideration

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.

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