Institutional Research and Analytics - Student Assistant

The Office of Institutional Research & Analytics is seeking a graduate student to assist in a project aimed at empowering campus stakeholders with advanced AI/LLM technologies. The ideal student will have basic experience in the following: programming skills, AI/LLM models, and data analysis and visualization.

Responsibilities include but not limited to, assist with data preprocessing, model development, interface design, and system deployment. Assist with evaluating and providing recommendations on new, current and planned database extractions, analyzing data and building reports/dashboards in support of educational effectiveness.

Under direct supervision, duties include but not limited to:
Assist in project(s) aimed at empowering campus stakeholders with advanced AI/LLM technologies. Data preprocessing, model development, interface design, and system deployment.

Evaluating and implementing recommendations on new, current and planned database extractions, analyzing data and building reports/dashboards in support of educational effectiveness.

• Ability to learn and perform assigned work; follow oral instructions; work cooperatively with faculty, staff, and other students; communicate effectively with all levels; and read and write English at a level appropriate to the position.

• Special Qualification: Admission or registration as a CSU student.

• Maintain a 2.0 G.P.A. or greater per semester and cumulative.
• Students must be enrolled in at least halftime units at CSUSB (6 units undergraduate; 3 units graduate)
• International students must have full-time enrollment at CSUSB. (12 units undergraduate; 6 units graduate)
• Eligible to work in the United States
• Payroll Requirement: Social Security Card

- Maintain a 2.5 G.P.A. or greater per semester and cumulative
- Must be able to work at least 2-3 days out of the work week (Monday - Friday)

Skills:
- Basic to intermediate proficiency in Python, essential for tasks involving data manipulation and analysis.
- Interest in AI/ML models, with exposure to or a desire to engage deeply with data analysis techniques, particularly those that involve AI applications.
- Demonstrated interest or experience in developing web-based applications, showing a capability to contribute to technical aspects of the project.

Experience:
- Participation in relevant coursework or projects.
- Experience with data analysis or related internships.
- Exposure to machine learning or AI projects (academic or personal).
Special Conditions:

Work status: Part-Time, Temporary, Seasonal

In our commitment to the furthering of knowledge and fulfilling our educational mission, California State University, San Bernardino seeks a campus climate that welcomes, celebrates, and promotes respect for the entire variety of human experience. We welcome people from all backgrounds, and we seek to include knowledge and values from many cultures in the curriculum and extra-curricular life of the campus community. We will create, promote, and maintain activities and programs that further our understanding of individual and group diversity. We will also develop and communicate policies and promote values that discourage intolerance and discrimination.

Reasonable Accommodation
We provide reasonable accommodation to applicants and employees with disabilities. Applicants with questions about access or requiring reasonable accommodation for any part of the application or hiring process should contact CSUSB Benefits at benefits@csusb.edu.

Smoking
CSUSB is a smoke and tobacco-free campus.  See policy https://calstate.policystat.com/policy/6591951/latest/.

Clery Act
In compliance with state and federal crime awareness and campus security legislation, including The Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act, California Education Code section 67380, and the Higher Education Opportunity Act (HEOA), the Cal State San Bernardino Annual Security and Fire Safety Report is available at: https://www.csusb.edu/clery-act.

Advertised: Sep 28 2026 Pacific Daylight Time
Applications close: Oct 27 2026 Pacific Daylight Time

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