Principal Data Scientist

The Role

Provides leadership and expertise to the Department regarding analytical and data solutions, by leading the development and integration of machine learning algorithms, statistical and AI models, and automation and process improvement initiatives to support innovation, improve service delivery, and inform business planning and strategy. Determines approach and selection of analytical methods and evaluates the operational, financial, service-level, workforce, and equity implications of analytical findings to support fiscally responsible program planning, resource allocation, and decision-making.

Partners with departmental business leaders to understand organizational challenges and provide evidence-based recommendations; supports business cases, investment decisions, grant and funding applications, and performance reporting by translating data into clear assessments of anticipated costs, benefits, risks, savings, service impacts, and return on investment. Designs and conducts experiments to support innovation, improve service delivery, and evaluate new approaches. 

Guides Epidemiologists, Health Data Analysts, and technical ITS teams in the building and maintaining of data pipelines and infrastructure; stays current with developments in data science, AI tools, and industry practices; and builds and refines machine learning and AI models to support prediction and decision-making. Ensures analytical solutions are prioritized and implemented in a manner that supports sustainable operating budgets, funding requirements, legislative obligations, and the effective use of public resources.

Duties/Responsibilities

• Performs data analysis using standard tools such as Python, SQL, R, and related technologies to support evidence-based decision-making across the Department. Develops analyses, forecasts, dashboards, and performance measures that inform operating and capital planning, service and program prioritization, workload and capacity planning. Identifies opportunities for efficiencies, cost avoidance, process redesign, and improved use of organizational resources.  
• Leads the management and coordination of Business Intelligence (BI), Artificial Intelligence (AI), and data warehouse activities, ensuring data systems, reporting environments, and analytical capabilities are effectively maintained and aligned with organizational needs. 
• Provides analytical leadership for business cases and decision materials related to data, analytics, automation, AI, and digital investments, including defining expected benefits, implementation costs, ongoing operating requirements, risks, dependencies, and measurable outcomes.  
• Supports the development, monitoring, and evaluation of externally funded initiatives, including grant applications, funding proposals, required performance measures, and reports to program areas, senior leadership, and Council, where applicable. Provides support and guidance to staff on data analysis and data visualization techniques and collaborates across teams to strengthen analytical practices and improve the quality and consistency of data use throughout the Department.
• Develops and applies machine learning techniques to support departmental priorities, automation projects, and other innovation initiatives. 
• Builds and refines machine learning and AI models to support prediction and decision-making; and works with Epidemiologists, Health Data Analysts, program managers, and other stakeholders to integrate analytical solutions into operations and service delivery.
• Provides expertise in statistical methods and research techniques. Supports the Research Ethics Board review process and delivers training in BI, AI, machine learning, data visualization, and data analysis, as required.  
• Assesses and prioritizes AI, machine learning, and automation opportunities based on organizational need, feasibility, privacy and security requirements, implementation effort, anticipated financial and operational benefits, impacts on staff roles and workloads, and alignment with approved priorities. 
• Develops and applies automation techniques using Microsoft data, analytics, automation, and workflow tools (e.g., Power BI, Power Query, Power Automate, SharePoint Lists, Forms, Power Apps, Microsoft 365 applications), to support reporting, workflow/process improvement, process automation, and decision-making.  
• Evaluates the impact of automation and analytical solutions on business processes, staff workload, skill requirements, role design, service delivery, and change-management needs. Establishes measures to evaluate whether implemented solutions achieve expected benefits (e.g., staff time saved, reduced manual effort, improved timeliness or quality, avoided costs, improved service outcomes, ongoing maintenance requirements).
• Recommends implementation approaches that support staff adoption, appropriate reskilling, and the responsible integration of technology into operational practices.
• Supports infectious disease surveillance and health status reporting, as needed.
• Liaises with post-secondary institutions to support collaborative research initiatives.

Additional Duties/Responsibilities

• Provides supervision and/or guidance to internal and external data engineers, co-op students or other staff as required, including assigning work, supporting development, and completing formal performance reviews. 
• Through technical leadership, staff collaboration, and operational support, plays a key role in advancing the Department’s analytical maturity and strengthening the integration of data-driven approaches into public health programs and services.  
• Provides input into staffing, resource, procurement, and work-prioritization decisions for the data and analytics function, consistent with approved budgets, delegated authorities, collective agreements, and organizational policies.  
• Monitors assigned project resources and identifies emerging financial, staffing, delivery, or operational risks requiring management attention or decision.
• Exercises professional and technical judgment in selecting analytical methods, establishing data-quality and model-evaluation approaches, prioritizing assigned analytical work, and recommending data, AI, automation, and reporting solutions within approved plans, policies, budgets, and delegated authorities.
• Makes recommendations to management and senior leadership on program performance, service demand, resource allocation, investment priorities, funding opportunities, operational risks, and the anticipated impacts of proposed changes.
• Identifies issues requiring escalation, including material privacy, legal, ethical, financial, service-delivery, reputational, workforce, or technology risks.
• Modifies or adapts broadly established methods and procedures as needed, within program, departmental, corporate, and legislative parameters. Develops practical solutions to diverse and complex problems, including situations where requirements may conflict, by applying sound/ professional judgment in alignment with best practices and legal frameworks. Consults with industry peers, other management, or senior leadership for significant or unique issues.
• Seeks out, assesses, and integrates relevant data, perspectives, and experience to make informed decisions and address operational and strategic challenges effectively. 
• Performs related duties as required.

Knowledge, Skills, and Abilities

• Knowledge is normally attained through a doctoral degree in Computer Science, Mathematics, or a related quantitative field. Equivalent combinations of education and experience may be considered.
• Knowledge of statistics and the application of statistical methods, which may include theories and principles of biostatics and epidemiology; big data, data manipulation, machine learning techniques, and data visualization tools and methods, plus progressively responsible related experience.
• Practical knowledge of analytical tools such as R, SQL, and/or Python. 
• Ability to maintain skills and keep current with developments in data science, AI tools, and industry practices.
• Ability to translate complex analytical results into practical recommendations that support senior-management decisions regarding program priorities, service levels, workforce capacity, investments, and funding opportunities. 
• Knowledge of and ability to comply with policies, procedures, professional standards, and related guidelines, standards, and legislation (e.g., Municipal Freedom of Information and Protection of Privacy Act, Personal Health Information Protection Act).
• Analytical and problem-solving skills to develop and implement solutions to support efficient operational practices and inform departmental planning and decision-making. Demonstrated ability in report writing, database maintenance, and project management. 
• Ability to work independently and manage multiple priorities.
• Leadership, communication, and collaboration skills to work effectively with, and provide guidance and support to program management and staff; exchange information and collaborate with corporate partners and industry peers; translate technical information into clear and useful insights for various stakeholders and senior management; participate as an effective team member. 
• Ability to prepare or contribute to decision briefs, business cases, budget submissions, funding proposals, and performance reports for technical and non-technical audiences.
• Ability to interpret findings and communicate results clearly to stakeholders, including senior leadership and cross-functional teams.
• Ability to travel within Waterloo Region. 
• Ability to support and demonstrate the Region’s values.