Associate Director, Business Intelligence

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Job Description:

Key Responsibilities:

•Build BI & Analytic Capabilities: Design and deliver business intelligence solutions that turn raw data into clear, visually compelling insights for end users across the university. Apply modern visualization platforms and predictive modeling techniques to make complex information accessible and actionable.

•Drive Analytical Rigor: Lead end-to-end analysis—from data sourcing through interpretation and prediction—to inform strategic priorities, financial planning, and investment decisions.

•Stay at the Forefront of the Field: Continuously sharpen expertise across analytic platforms, database environments, and emerging technologies. Bring fresh approaches to Furman by evaluating new tools, methodologies, and AI-driven capabilities relevant to higher education.

•Set the Standard for Quality: Establish and uphold consistency, accuracy, and professionalism across all analytical deliverables. Define team-wide best practices that ensure outputs are reliable, repeatable, and aligned with institutional priorities.

•Strengthen Financial Sustainability: Provide deep-dive analysis on institutional spending patterns, endowment performance, and revenue dynamics to support a resilient, forward-looking financial environment.

•Champion AI Integration: Spearhead the thoughtful adoption of AI tools throughout administrative operations—discovering where automation, predictive insight, and intelligent reporting can deliver measurable outcomes.

•Coordinate Across Departments: Act as the central point of coordination between IT, Finance, and the Investment Office, ensuring data quality, security, and seamless integration.

Required Qualifications

•Experience: Minimum 5+ years in business intelligence, data analytics, or a closely related field—preferably within a complex institutional or financial environment.

•Education: Bachelor's in Data Science, Finance, Economics, Statistics, or a related quantitative field. Master's preferred.

•Technical Expertise: Strong command of modern data visualization software, predictive modeling languages, SQL, and Python. Familiarity with CRM-based analytics environments is a plus.

•Analytical Skills: Demonstrated ability to synthesize large, complex datasets into clear, executive-level insights.

•Communication: Exceptional ability to translate technical findings into strategic recommendations for non-technical senior leadership.

•Leadership: Proven track record of setting best practices and quality standards across an analytical team or function.

Preferred Qualifications

• Experience in higher education administration or endowment management.

• Familiarity with AI and machine learning techniques applied in financial or operational settings.

• Working knowledge of major financial databases and cloud-based data platforms.

• Demonstrated success leading cross-functional initiatives with multiple departmental stakeholders.

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