Master’s degree in Data Science, Mathematics, Analytics, or a related field.
Job Duties:
Design and conduct advanced data analyses on institutional datasets related to student enrollment trends, academic performance, student engagement, and program effectiveness using SQL, Python, and statistical analysis tools.
Develop, test, and refine analytical and predictive models to evaluate relationships between student characteristics, learning modalities, and academic outcomes, supporting evidence-based institutional planning and decision-making.
Apply quantitative and statistical techniques, including regression analysis, segmentation, and predictive trend analysis, to identify factors influencing student retention, academic success, and program performance.
Integrate data from multiple institutional sources, including enrollment systems, learning management platforms, and international program reports, to produce comprehensive analytical insights and performance assessments.
Create advanced dashboards, visualizations, and analytical summaries that translate complex modeling results into actionable insights for academic leadership and administrative stakeholders.
Advise internal teams on data interpretation, analytical assumptions, and appropriate application of statistical findings to support institutional planning, resource allocation, and program improvement initiatives.
Evaluate data quality, analytical methodologies, and reporting frameworks to ensure the accuracy, reliability, and relevance of institutional analyses.
Develop and maintain standardized analytical workflows, reusable queries, and documented processes to improve efficiency, consistency, and scalability of institutional data science practices.
California University Preparatory Academy (CUPA) is a U.S.-based college-preparatory institution headquartered in Redlands, California, founded to serve the academic advancement needs of domestic and international K–12 students. The institution specializes in flexible, university-aligned educational programs delivered through both online and in-person learning formats.
As CUPA expands its enrollment and academic offerings, the ability to collect, analyze, and interpret institutional data has become increasingly important. With growing volumes of academic performance, enrollment, and program engagement data, robust data analysis capabilities are essential to maintaining operational accuracy and supporting evidence-based institutional decision-making.