Business Intelligence Analyst

Post University•Waterbury, CT

About The Position

The Business Intelligence Analyst supports institution-wide, data-informed decision making by transforming academic, enrollment, and operational data into actionable insights for senior academic and administrative leaders. Reporting to the Senior Director of Project Management and Business Services, this critical role blends traditional business intelligence functions—reporting, dashboarding, and data validation—with advanced analytics, predictive modeling, and emerging AI-enabled analytic workflows. The ideal candidate is equally comfortable working with structured institutional datasets (e.g., enrollment, retention, financial aid, LMS activity) and applying statistical, predictive, and prescriptive techniques to support student success, academic planning, accreditation, and operational efficiency. This position works closely with academic leadership and non-technical stakeholders and serves as a trusted analytics partner supporting students, academic planning, and operational excellence across the institution.

Requirements

Bachelor’s degree in Data Science, Statistics, Computer Science, Business Analytics, Institutional Research, or a related field with a proven record of data analytics/data science professional experience.
Demonstrated experience with Power BI, Excel, and Statistical analysis and data modeling techniques.
Detail-oriented with strong verbal and written communication skills with the ability to convey complex concepts to technical and non-technical audiences.
Demonstrated analytical problem-solving skills with the ability to challenge the assumptions.
Ability to prioritize and manage multiple projects and deadlines in a remote work setting.

Nice To Haves

Master’s degree in Data Science, Applied Analytics, Statistics, or related field.
Experience working in higher education, institutional research, enrollment management, student success analytics.

Responsibilities

Collect, clean, structure, validate, and analyze institutional data from SIS, LMS, CRM, HRIS, financial systems, and other sources of data.
Translate complex data into actionable insights through visualizations, summaries, and presentations, making it easy for business partners to grasp the information, and ensuring the insights are accessible to non-technical audiences.
Develop and deploy predictive models to forecast enrollment, retention, student risk, course demand, and operational outcomes.
Conduct ad‑hoc studies for internal stakeholders related to program performance, student outcomes, faculty productivity, resource planning, and assessment.
Design, test, and operationalize prompts and workflows for generative AI assistants (e.g., Microsoft Copilot, Google Gemini, ChatGPT, and other AI tools) to accelerate analyses, draft summaries, and create first‑pass insights.
Identify high‑frequency manual reporting tasks that can be automated with AI (summaries, classification, entity extraction), freeing capacity for deeper analysis and stakeholder engagement.
Interact with the business to understand business processes and data flows that impact analytic solutions.
Perform root cause analysis and present findings to both technical and non-technical audiences.
Work cross‑functionally with academic deans, faculty, enrollment leaders, student support teams, and technology departments.
Provide training or consultation on data literacy, performance metrics, and dashboard interpretation.
Contribute to data governance initiatives.
Assist in creating and maintaining data pipelines, documentation, and data dictionaries.
Any additional tasks requested