Director OF DATA Analytics Institutional Research

Director of Data Analytics, Institutional Research

Boston University Information Services & Technology (IS&T) is seeking applicants with diverse skills and experiences to join our innovative and inclusive community. The Director of Data Analytics is a technically proficient and strategic leader responsible for designing and delivering a sophisticated analytics program that supports data‑informed decision‑making by senior leadership and central administration at Boston University. This position requires deep technical fluency in Python, SQL, machine learning, and statistical modeling, alongside the ability to translate advanced analyses into actionable institutional insights.

The Director delivers high‑impact data products including predictive models, statistical analyses, executive dashboards, and scenario simulations to support institutional planning, resource allocation, policy development, and performance assessment. This role is critical in advancing a modern, scalable analytics infrastructure and in developing cutting‑edge models that directly inform areas such as enrollment forecasting, student success, and operational optimization. In collaboration with the Data Engineering team and analysts in Analytical Services & Institutional Research, the Director contributes to the University Data Library an integrated resource offering coordinated access to data, reports, and business intelligence tools.

The role is essential to enrollment management and institutional forecasting, providing robust, technically sound models and decision frameworks that support the financial sustainability of the university. The Director leads a team of analysts and works across academic and administrative units to foster a culture of advanced analytics and evidence‑based planning aligned with Boston University's strategic goals.

Full‑time / Regular

BOSTON, MA, United States

$ – $ (Grade 53)

• Advanced Analytics & Insight Generation:
  Develop predictive models and machine learning algorithms to support strategic initiatives such as student success, enrollment forecasting, and space optimization. Extract actionable insights from complex datasets to inform university‑wide decisions.
• Analytics and Data Infrastructure:
  Build scalable analytics tools, automated reporting and processes, and secure reporting environments. Collaborate across departments to enhance data access, governance, and integration for improved decision‑making.
• Reporting and Insight Delivery:
  Deliver clear, tailored reports and dashboards for senior leadership, ensuring accuracy and relevance in KPI tracking, benchmarking, and compliance.
• Leadership and Team Development:
  Lead and mentor analytics staff, promote best practices in data science, automation, and foster collaboration across academic and administrative units.
• Stakeholder Engagement:
  Serve as a liaison to campus and external groups, and champion data literacy among non‑technical stakeholders.

• Bachelor's degree in statistics, data science, computer science, applied mathematics, higher education, or a related field.
• Master's or PhD preferred but not required.
• 8+ years of progressively responsible experience in data analytics, data science, or institutional research.
• Advanced proficiency in Python, SQL, and R for data modeling, cleaning, and analysis.
• Hands‑on experience with machine learning frameworks and statistical modeling.
• Proficiency in data visualization platforms and programming libraries (e.g., Tableau, Power BI).
• Strong understanding of data engineering practices, including pipeline design, version control, and workflow orchestration.
• Exceptional communication skills with the ability to articulate complex analyses to non‑technical audiences and senior leadership.
• Demonstrated success leading analytic teams and managing high‑impact, cross‑departmental projects.

• Higher education experience is ideal but not required.
• Demonstrated experience with enrollment management concepts, modeling, and applications.
• Experience in an R1 university or similarly complex academic institution.
• Familiarity with higher education data systems (e.g.,…