Job Description
Marshall University is seeking a skilled Business Intelligence and Data Analyst to join our Institutional Research team. This role is pivotal in supporting the university’s strategic decision-making processes by providing actionable insights from data. The ideal candidate will have a strong foundation in data analysis, business intelligence tools, and a passion for transforming data into meaningful narratives that aid in institutional planning and policy formulation. The successful candidate will work collaboratively with the Institutional Research and Planning team, as well as other university departments, leveraging analytical and technical skills to drive data-driven strategies.
Key Responsibilities:
Data Architecture and Advanced Analytics

• Design and maintain scalable data models and reporting structures to support enterprise analytics.
• Develop, validate, and refine predictive and forecasting models related to enrollment, retention, student success, and financial planning.
• Perform advanced statistical analyses to evaluate program effectiveness, student outcomes, and institutional performance metrics.
• Optimize SQL queries for performance and reliability within relational database environments (Oracle).

Business Intelligence Development

• Develop enterprise dashboards, semantic models, and analytical reporting solutions in Power BI (or comparable BI platforms).
• Develop and maintain DAX measures, optimized data models, and star schema designs to support scalable reporting.
• Automate recurring reporting processes and enhance reproducibility of analytics workflows.

Enterprise-Level Data Expertise

• Extract, transform, and analyze data from enterprise-level systems (e.g., Banner or comparable systems).
• Support preparation and validation of federal and state reporting (e.g., IPEDS and other compliance reporting).
• Apply understanding of complex enterprise data systems and relational databases (e.g., academic, financial, and HR data structures in analysis and reporting).

Data Governance and Quality Assurance

• Contribute to institutional data governance initiatives, including data definitions, documentation, and standards development.
• Implement and monitor quality control processes to ensure data accuracy, integrity, and consistency.
• Enhance data infrastructure and reporting capabilities.

Salary Range $60,441 - $78,574 commensurate with experience, education, and internal equity.
Salary Type Salary
Time Type Full-Time
Work Location MU - Marshall University
Qualifications
Must be able to perform all essential job duties as outlined in the job description.
Required Qualifications
Education
Bachelor’s degree in a quantitative, analytical, or technical field required (e.g., data science, statistics, computer science, information systems, mathematics, economics, or similar discipline)

Experience
2+ years of progressive experience in business intelligence, analytics, or institutional research
Experience working with complex enterprise data systems and relational databases
Demonstrated proficiency in SQL for querying, transforming, and analyzing large relational datasets
Experience developing dashboards, reports, or analytical visualizations using a business intelligence platform
Experience working with relational database environments and structured data models
Ability to design, validate, and interpret analytical or predictive models to support data-driven decision making
Experience working with complex enterprise data systems and integrating data from multiple sources

Preferred Qualifications
Education
Master’s degree in a quantitative field

Experience
Experience working with higher education administrative systems (e.g., Banner or similar ERP systems)
Experience supporting federal or state reporting (e.g., IPEDS)
Experience working with Oracle or other enterprise relational database systems
Experience developing dashboards, semantic models, and measures in Power BI
Experience working with dimensional or star schema data models in a data warehouse environment
Experience using statistical or programming tools such as Python or R for data analysis or modeling
Experience building predictive, forecasting, or statistical models