Data Scientist - Applied AI, VP Development and Alumni

Position overview

Analytics program leadership

• Develop an advanced analytics and applied AI program with the Manager, Data Systems to support university-wide and faculty fundraising, communications, and engagement.
• Identify issues with D&A teams, develop solutions, and generate insights from internal and external data.
• Build organizational analytics capacity through training and workshops; mentor Reporting Analysts.

Modeling, AI, and fundraising analytics

• Lead analytics projects and align their objectives with organizational vision and strategy.
• Design, implement, and evaluate generative AI solutions, including LLMs, RAG, semantic search, and agentic workflows; evaluate approaches for value, cost, fit, maintenance, privacy, security, and integration.
• Build predictive, behavioral, and AI-assisted solutions to increase revenue, save time, and improve ROI.
• Deliver analytics for contact acquisition, donation conversion and value, engagement, and constituent segmentation.
• Develop visual intelligence tools and applications and make data science initiatives accessible to end users.
• Analyze large and unstructured datasets to identify constituent pools, patterns, trends, and underlying causes.
• Use internal databases and external sources such as screening services, census records, surveys, and marketing data.
• Coordinate reports, visualizations, interfaces, and analysis with the Advancement Data team, including recommendations.
• Manage model imports to Blackbaud CRM and support reliable data extraction and API-based integration.
• Partner with business users on solution design, implementation, adoption, continuous improvement, feedback, and measurement of business value.

Knowledge and other duties

• Monitor developments in data science, business intelligence, philanthropy, and higher education, and share relevant information with department and senior leadership.
• Perform other duties as assigned.

Qualifications and experience

• Graduate degree required, with demonstrated competencies in data science, predictive modeling, fundraising analysis, machine learning, applied AI, research, or similar fields.
• Demonstrated analytical, project design and management, and creative problem-solving skills.
• Ability to synthesize large, complex datasets, extract actionable insights, and explain them clearly to varied stakeholders using visualization tools.
• Proven ability to build, implement, and optimize predictive data models.
• Experience with LLMs, RAG, embeddings, vector search, AI agents, or agentic workflows is preferred.
• Advanced statistical, big data, machine learning or AI, and data-mining experience; highly proficient scripting skills, including Python for data processing, automation, and API integration.
• Expertise in analytical applications, program development, evaluation methodologies, and evaluating analytical and AI solutions.
• Intermediate to advanced data management, database design, and Transact-SQL querying.
• Professional experience with SQL Server and SSIS, SSRS, IIS, and Visual Studio.
• Microsoft Fabric, GitHub Copilot, Claude Code, OpenAI, or comparable cloud data and AI platforms are preferred assets.
• Strong interpersonal, written, and oral communication; mentoring and training experience in data science; commitment to sharing skills with colleagues.

Additional qualifications

• Professionalism, ethical sensitivity, discretion, and commitment to confidentiality.
• Ability to manage multiple projects and priorities and meet changing deadlines.
• Previous analytical experience in a complex development or fundraising environment, preferably post-secondary, is a preferred asset.

Office context

Application details

• Application deadline: November 2, 2026.