Job Requisition ID:


Time Type:
Full time

Employee Group:
Staff

Job Category:
Analytics and Reporting

Employment Type:
Temporary

Department:
Faculty of Mathematics - Dean of Mathematics Office - Data

Hiring Range:
$73,695.42 - $92,119.28

Posting Information:This posting is for an existing vacancy.

The internal posting deadline for this position is September 3, 2026 at 11:59PM

This position is being offered as a Secondment or contract opportunity. Term: 2 years

Job Description:

Primary Purpose

The Data Analyst will advance the Faculty of Mathematics' use and integration of data to inform decision-making and improve operational efficiency. The Data Analyst is responsible for understanding, consolidating and analyzing data about the Faculty of Mathematics and for effectively communicating analyses and findings. The Data Analyst will maintain a robust understanding of data systems and of University and Faculty policies and practices to be able to understand the needs of a variety of clients across the Faculty and to design and develop effective data solutions.

Key Accountabilities

Data Management
• Ensure Faculty data is accurate, consistent, properly maintained and shared in compliance with relevant privacy protection, confidentiality and other ethical principles.
• Identify and address data integrity/reliability issues and use data cleaning processes to achieve required data quality standards and identify data anomalies and discrepancies to appropriate institutional data stewards.
• Understand the available data, systems, dictionaries, and distribution channels from multiple information systems across the University and involving multiple domains.
• Execute and develop new Python scripts that enable data-informed operational processes for Faculty service units.
• Design and implement dimensional models across multiple subject areas for analytics solutioning.
• Create and maintain documentation as needed.

Data Analysis and Reporting
• Independently work with varied clients to identify, clarify, and fully understand their questions or problems, determine appropriate analytical approaches, and develop effective data solutions
• Develop and apply deep understanding of University and Faculty policies, procedures, and guidelines (including but not limited to undergraduate studies regulations) to solution design and analysis.
• Analyze data using advanced statistical techniques (regression, clustering, decision trees etc.) to gain insights.
• Independently develop and apply reliable forecasting, predictive, and "what-if" models to address business questions and inform and support planning, evaluation, and budgeting processes.
• Assess and determine the appropriateness of machine learning algorithms, and other techniques to address business problems and optimize data solutions.
• Develop reports and relevant data visualizations (including dashboards, graphs and presentations and web applications) to inform evidence-based decision-making in the Faculty.
• Maintain Faculty-wide business intelligence reporting, ensuring consistent quality control practices and most recent data available.
• Develop queries using efficient SQL, applying expert understanding of databases and sound judgment of business requirements.

Communication
• Provide advice and recommendations based on data analysis, modelling, and interpretation of risks and opportunities
• Communication findings, recommendations, and data through reports, presentations, and visual analytics to support evidence-based decision-making
• Research new tools, systems, and practices to recommend improvements across all domains of the role.
• Understand the needs of each stakeholder group in order to assess and scope projects fully and to make recommendations on timelines and priorities for each.
• Communicate effectively with multiple, varied clients (senior leadership, faculty members, and staff) to understand needs, scope projects and project terms, update progress, and present findings.
• Ensure data and information is placed into the proper context by combining university data with both qualitative and quantitative environmental/external data and appropriate narrative.

Required Qualifications

Education
• Degree in computer science, statistics, mathematics, data science, economics , or another related discipline is required. An equivalent combination of education and experience may be considered.

Experience
• 3+ years' experience in work related to data management, data analytics, statistical analyses and predictive modelling.

Knowledge/Skills/Abilities
• Proven ability to write SQL queries and to use SQL or other tools to extract, transform and load data for analysis.
• Proven ability to use R, Python, or equivalent for data analysis and visualization.
• Proven ability to use Python or another scripting language to automate tasks.
• Knowledge of statistical packages, ETL methods, and visual analytics.
• Demonstrated ability to streamline and automate processes.
• Critical thinking skills and a natural curiosity to understand processes and data relationships.
• Strong interpersonal, visual, and technical written communications skills.
• Effective collaborator, able to work with a variety of technical and non-technical roles across teams.
• Strong stakeholder management and prioritization skills.
• Experience with Microsoft Fabric or Power BI would be an asset.
• Knowledge of postsecondary education data domains or student data systems would be an asset.