Data Scientist, Student Success Analytics

James Madison University•Harrisonburg, VA

About The Position

Student Success Analytics at James Madison University is seeking a Data Scientist for an applied analytics and research role focused on turning student-success data into ethical, actionable evidence for institutional decisions. The position reports to the Director and joins a team that includes another data scientist and a data engineer. It supports the strategic goal of advancing data maturity to maximize student-success outcomes. The Data Scientist will help shape how data is designed, collected, and used to support student success and retention. During JMU’s enterprise-wide system modernization, the role offers opportunities to contribute to data ethics, analytics, and data-informed decision-making. The position will help advance a student-success culture informed by data from systems such as the Customer Relationship Management (CRM), Learning Management Software (LMS), Student Information System (SIS), and other sources. The role works closely with Student Affairs, Planning, Analytics, & Institutional Research (PAIR), Information Technology, The Graduate School, the Libraries, and other departments. It contributes to a campus knowledge community developing expertise in data maturity and integrating data science into leadership decisions. The position is telework eligible.

Requirements

Master’s degree in Statistics, Computer Science, Operations Research, Mathematics, Physics, Finance, or another quantitative discipline.
Proficiency in SQL and at least one statistical or general-purpose programming language; Python or R preferred.
Experience using statistical methods and programming languages to manage data and generate insights from large datasets.
Experience analyzing, summarizing, and clearly communicating information, including knowledge of open-source or commercial data visualization libraries or tools.
Ability to work in a highly collaborative and dynamic work environment.
Awareness of and commitment to data privacy, security, and ethics.
Awareness of and commitment to the ways data analytics can strengthen student success, retention, and graduation across student populations.

Nice To Haves

Experience in higher education.
PhD in Statistics, Computer Science, Operations Research, Mathematics, Physics, Finance, or another quantitative discipline.
Experience creating and using advanced machine-learning algorithms and statistical methods, including regression, simulation, modeling, clustering, and decision trees.
Professional experience in equitable data management, data use, and data analytics.
Experience working with relational and non-relational database systems.
Experience using, building, and deploying generative AI tools.

Responsibilities

Analyze data to generate actionable insights for the early student success team and other stakeholders.
Design and evaluate descriptive, predictive, and, where appropriate, causal or quasi-experimental analyses; document assumptions, uncertainty, limitations, and differential performance across student populations.
Communicate analytical insights through visualizations, presentations, written reports, publications, and other multimedia.
Collaborate with Student Academic Success partners and colleagues across campus on data management best practices, data ethics and privacy, data-informed research questions, and data use.
Advocate for privacy, ethics, and equity in decisions about the design, management, and use of data for the early student success system.
Explore and evaluate responsible uses of generative AI for analytical workflows, knowledge retrieval, documentation, and decision-support tools, with attention to privacy, accuracy, accessibility, and human oversight.