Data Scientist

James Madison University; Harrisonburg (VA); Hybrid; USD 85,000 - 120,000; Full time

Job summary

James Madison University’s Student Academic Success Analytics team seeks a Data Scientist to turn student-success data into ethical, actionable evidence that improves learner outcomes. This hybrid role in Harrisonburg, VA focuses on applied analytics and research, partnering across campus to enable data-informed decisions, including responsible exploration of AI in workflows.

The role emphasizes collaboration, data privacy, and equity across student populations and uses statistical methods to

Qualifications

• MS in a quantitative field.
• Proficiency in SQL and at least one programming language (Python or R).
• Experience using statistical methods to manage data and generate insights from large datasets.
• Ability to communicate results with visualizations and reports.
• Awareness of data privacy, ethics, and collaborative work.

Responsibilities

• Analyze student-success data to produce actionable insights for early success teams.
• Design descriptive, predictive, and possibly causal analyses with documented assumptions.
• Communicate results via visualizations, presentations, and reports.
• Collaborate across campus on data governance, privacy, and ethics.
• Explore responsible uses of generative AI in analytics workflows.

Skills

SQL

Python

R

Data visualization

Open data ethics

Education

MS in Statistics, CS, OR, Math, Finance, or other quantitative discipline

PhD in Statistics, CS, OR, Math, Physics, Finance, or other quantitative discipline

Tools

Generative AI

Relational and non-relational databases

Job description

James Madison University’s Student Academic Success Analytics (SSA) team is seeking a Data Scientist to turn student-success data into ethical, actionable evidence that supports improved outcomes for learners. This hybrid role in Harrisonburg, VA focuses on applied analytics and research, partnering across campus to enable data-informed decision-making, including responsible exploration of generative AI in analytical workflows.

What you will do

• Analyze student-success data to produce actionable insights that help the early student success team and other stakeholders take data-driven action.
• Design and evaluate descriptive, predictive, and, where appropriate, causal or quasi-experimental analyses, while documenting assumptions, uncertainty, limitations, and differential performance across student populations.
• Communicate results through visualizations, presentations, written reports, publications, and other multi-media formats.
• Collaborate with Student Academic Success (SAS) partners and colleagues across campus on data management best practices, including data ethics and privacy, data-informed research questions, and the use of data.
• Advocate for data privacy, ethics, and equity as central to the design, management, and use of data for the early student success system, including work with the broader campus community.
• 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.

Required qualifications

• MS 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, preferably Python or R.
• Experience using statistical methods and programming to manage data and generate insights from large data sets.
• Experience analyzing, summarizing, and communicating information clearly, including knowledge of open source or commercial data visualization libraries or tools.
• Ability to work in a collaborative, fast-moving environment.
• Awareness of and commitment to data privacy, security, and ethics.
• Awareness of 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 another quantitative discipline.
• Experience creating and using advanced machine learning algorithms and statistics such as regression, simulation, modeling, clustering, and decision trees.
• 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 AI tools.

Tools and technologies

• SQL
• Python
• R
• Generative AI

Location and work arrangement

• Harrisonburg, VA (hybrid)
• Telework eligible

Conditions of employment

• Employment is contingent upon successful completion of a criminal background check.
• After accepting employment, new hires must complete an I-9 form and provide documentation of identity and eligibility to work in the United States.
• James Madison University uses the E-Verify system to confirm identity and work authorization.

Additional information

• JMU’s Dual Career and Community Resources Program is available for candidates relocating to the area.
• Reasonable accommodation: If you are an individual with a disability and need assistance searching or applying for jobs, contact [phone] or [e-mail].