Job Specifications
Date Posted: 09/18/2025
Req ID: 45200
Faculty/Division: VP - Division of University Advancement
Department: Advancement Services
Campus: St. George (Downtown Toronto)
Position Number: 00045324
Description
About us:
The Division of University Advancement (DUA) aims to sustain and enhance the University of Toronto's academic mission, leadership, and worldwide impact, by engaging alumni and private sector constituents meaningfully in the mission of the University, building mutually beneficial relationships of increasing value and satisfaction over time.
DUA at the University of Toronto is engaged in a transformative agenda deeply rooted in the University's vision for growth and innovation. We are focus on growing fundraising efforts? enhancing the effectiveness and satisfaction of alumni engagement and programs? building advancement talent capacity within and across divisions; creating an organization and culture that fosters diversity and inclusiveness.
Your Opportunity
The Business Intelligence unit within DUA plays a pivotal role in advancing strategic decision-making and elevating the effectiveness of development efforts. By transforming complex data into actionable insights, the unit supports leadership in setting priorities, identifying high potential prospects, and tracking performance across campaigns and programs. Additionally, the BI team
provides thought leadership by shaping data-informed strategies, developing predictive models, and guiding the organization toward long-term, sustainable fundraising growth.
Reporting to the Director, Business Intelligence and Analytics, the incumbent will provide strategic technical expertise in data analysis, predictive modeling, and AI-driven insights. This includes technical project management activities such as scope, timeline estimation, and expectation management; liaison with data stewards and custodians to ensure validity and integrity of the data and BI solutions provided and establishes design standards and best practices that foster complex analysis, information exploration and data-enabled decision making by all clients.
This position requires a blend of business intelligence, analytics, AI expertise, and stakeholder collaboration to develop and deliver best in class innovative data solutions that align with the university's advancement priorities, while fostering our Advancement values: Authentic Collaboration, Grateful Mindset, Intentional Inclusion, Trust and Transparency, Driving Impact.
Your Responsibilities Will Include
Conducting detailed data analysis to inform management decision making
Conducting data modelling for predictive analysis
Assessing and determining benchmarks and metrics for alumni programming and advancement activities
Analyzing the effectiveness of campaigns and/or programs
Advising clients and technical subject matter experts on best practice for documenting business requirements
Probing for information to determine requirements for ad hoc data requests
Essential Qualifications
Bachelor's Degree in Geography, Urban Planning, Economics, Computer Science; or acceptable combination of equivalent experience. Courses in business process management or project management are an asset.
Minimum five (5) years of relevant experience with manipulating, transforming, and analyzing complex, high-volume, high dimensionality data from varying sources.
Direct experience in a fundraising/not-for-profit environment; specifically, familiarity with annual giving, major gift and planned giving prospect identification and acquisition strategies.
Direct experience and demonstrated expertise to leverage proven techniques to elicit and analyze client needs; ability to provide key input into solutions that meet and often exceed client needs.
Exhibit strong experimental design skills used in practice, including research questions and research design, statistical hypothesis testing, linear regression, classification, resampling methods, linear model selection and regularization, non-linear regression, tree-based methods, support-vector machines, unsupervised learning, experimental contrasts, factorial experiments, and within-subjects experiments.
Direct experience and demonstrated expertise interpreting business objectives and drivers to shape initiatives to deliver metric driven outcomes that fulfill these business objectives Including choosing and executing appropriate experimental design based on the given data science project.
Direct experience and demonstrated expertise with manipulating, transforming, and analyzing complex, high-volume, high dimensionality data from varying sources.
Direct experience and demonstrated expertise required on Blackbaud CRM.
Direct experience and demonstrated knowledge and skills in a wide range of technologies, tools, and methodologies as applied within a high availability distributed environment: Relational databases (MS SQL Server, Oracle, DB2); Data management tools (MS SQL Server BI Stack: Visual St