Data Scientist, Student Success Analytics

Student Success Analytics (SSA) at James Madison University is accepting applications for a Data Scientist as part of its work toward leveraging data and technology for improving student success and retention. The Data Scientist is an applied analytics and research position focused on transforming student-success data into ethical, actionable evidence for institutional decisions. This position reports to the Director, works on a team within another data scientist and data engineer, and supports the strategic vision to achieve the highest level of data maturity that maximizes success outcomes for all students.

The Data Scientist will help shape the design, collection, and use of data and data analytics to ensure student success and retention. JMU is in the middle of an enterprise-wide system modernization program, and this position has unique opportunities to shape the paths forward for data ethics, data analytics, and the use of data for student success and data-informed decision-making. This position will help lead efforts as the university moves forward in establishing a student success culture informed by data from the Customer Relationship Management (CRM), Learning Management Software (LMS), Student Information System (SIS), and other systems.

The Data Scientist will work closely with Student Affairs, Planning, Analytics, & Institutional Research (PAIR), Information Technology, The Graduate School, the Libraries, and other departments. The person in this position would be joining at an exciting time as efforts are underway to build a knowledge community that develops and enhances expertise around how JMU will work toward a data maturity model that integrates data science into leadership decisions.

This position is telework eligible.

Duties and Responsibilities:

Analyze data to generate actionable insights that can empower the early student success team and other stakeholders to act on data

Design and evaluate descriptive, predictive, and, where appropriate, causal or quasi-experimental analyses; document assumptions, uncertainty, limitations, and differential performance across student populations

Communicate insights from data analysis through visualizations, presentations, written reports, publications, and other multi-media

Collaborate with Student Academic Success (SAS) partners and colleagues across campus on data management best practices, data ethics and privacy, data-informed research questions, and the use of data

Advocate for data privacy, ethics, and equity as central in any design, management, and use of data decisions for the early student success system, including in collaboration with colleagues across the campus community

Explore and evaluate responsible uses of generative AI for analytical workflows, knowledge retrieval, documentation, and decision-support tools, with appropriate attention to privacy, accuracy, accessibility, and human oversight

MS in Statistics, Computer Science, Operations Research, Mathematics, Physics, Finance, or other quantitative disciplines

Proficiency in SQL and at least one statistical or general-purpose programming language, preferably Python or R.

Experience with statistical methods and programming language to manage data and provide insights from large data sets

Experience analyzing, summarizing, and communicating information clearly, including knowledge of open source or commercial data visualization libraries/tools

Ability to work in a highly collaborative and dynamic work environment

Awareness of and commitment to the value of data privacy, security, and ethics

Awareness of and commitment to how data analytics can strengthen student success, retention, and graduation across student populations.

Preferred Qualifications:

Experience in higher education

PhD in Statistics, Computer Science, Operations Research, Mathematics, Physics, Finance, or other quantitative disciplines

Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, modeling, clustering, decision trees, etc.

Professional experience in equitable data management, use of data, and data analytics

Experience working with relational and non-relational database systems

Experience using, building, and deploying generative A.I. tools

Mission We are a community committed to preparing students to be educated and enlightened citizens who lead productive and meaningful lives.

Vision To be the national model for the engaged university: engaged with ideas and the world.

Who We Are Situated in the heart of Virginia’s beautiful Shenandoah Valley, the city of Harrisonburg is a vibrant community with a population of approximately 52,000. Harrisonburg is conveniently located approximately 120 miles from Washington, D.C. and Richmond, VA.

JMU is a selective, public institution with a growing national reputation for offering experiences that lead to an outstanding education and supportive environment for students, faculty and staff. The student body includes approximately 21,000 undergraduate and 1,800 graduate students, with over 1,000 full-time instructional faculty.

JMU offers thriving programs in the liberal arts, science and technology, and professional disciplines at the undergraduate, master’s and doctoral levels. JMU has achieved national recognition for the high quality of its academic programs, focus on maintaining strong student/faculty interaction, and innovative faculty research.