Top Data Analytics Jobs in Toronto

Leads GS1 Canada’s enterprise business intelligence, analytics, market intelligence, KPI framework, and AI-enabled transformation. Builds and manages the analytics function, develops predictive and decision-oriented insights, supports executive and Board reporting, and partners cross-functionally on subscriber growth, retention, adoption, performance, and market opportunities. Establishes governance, responsible AI practices, measurement standards, and team capabilities while translating complex data into strategic recommendations.

Leads the Sponsor Analytics function for Group Benefits, overseeing sponsor-facing reporting, dashboards, self-service analytics, data products, and actionable insights. Partners with sponsors, Distribution, Product, Operations, Data, and Technology teams to establish analytics strategy, improve data quality and governance, automate scalable reporting, and support business decisions. Manages and develops a high-performing analytics team while advancing data storytelling, innovation, stakeholder value, and analytics capabilities across portfolio, customer, member, and operational priorities.

Leads resourcing governance insights for Product Development Data Sciences by consolidating workforce, financial, sourcing, portfolio, and operational data. Develops executive analyses, presentations, scenarios, recommendations, and competitive intelligence to support resource decisions. Monitors trends, risks, anomalies, and capacity needs while partnering with operations and analytics infrastructure teams to improve data quality, dashboards, automation, and advanced analytics.

Manage and expand distributor, reseller, and systems integrator partnerships across Eastern Canada. Develop strategic account plans, drive partner pipeline and revenue, oversee forecasting and account mapping, enable partners, coordinate virtual marketing, sales, and technical teams, and serve as the liaison between channel partners and Trellix sales leadership. The role focuses on enterprise, commercial, and government segments and requires cybersecurity marketplace knowledge and channel sales experience.

Develop scalable business intelligence and reporting solutions across marketing, loyalty, merchandising, and promotional initiatives. Responsibilities include integrating enterprise data, building automated pipelines, creating dimensional and semantic models, developing Power BI dashboards and DAX calculations, analyzing business performance, ensuring data quality, and communicating insights to stakeholders. The role requires strong SQL, Power BI, data modeling, Python or PySpark, and cloud analytics experience.

Manages stress testing analytics, enterprise reporting, and risk data initiatives. Aggregates, maps, reconciles, validates, and analyzes large datasets; consolidates model results; applies analytical adjustments; and transforms complex outputs into visualizations and presentations for senior stakeholders. The role supports credit risk, loss forecasting, lending products, and stress testing while using Power BI, Excel, and PowerPoint, with potential Python, SQL, and SAS applications. It also provides analytical support, recommendations, and data-driven insights across technical and business teams.

Develop scalable business intelligence and reporting solutions across marketing, loyalty, merchandising, and promotional initiatives. Responsibilities include integrating enterprise data, building automated pipelines and analytical datasets, designing dimensional and semantic models, creating Power BI dashboards and advanced DAX calculations, analyzing business performance, ensuring data quality, and communicating insights to stakeholders. The role requires strong SQL, Power BI, data modeling, cloud analytics, and stakeholder communication skills.

Analyze full-funnel B2B marketing performance using dashboards, SQL, attribution modeling, and CRM data. Build Tableau or Looker Studio reporting, query Redshift data, and apply Python, AI APIs, prompt engineering, and automation to streamline data processing and performance summaries. Partner with campaign, web, and sales operations teams to improve tagging, KPI consistency, lead velocity, and conversion insights.

Leads senior client relationships and multiple concurrent engagements, owning delivery outcomes, engagement economics, team development, executive communication, and account growth. The Principal guides consulting and AI engineering teams, translates client priorities into solutions, manages scope and profitability, develops new opportunities, and contributes to firm strategy. The role emphasizes business judgment, people leadership, technical fluency, and trusted-advisor relationships with private equity sponsors and portfolio-company executives.

Leads analytics, reporting, digital health, and clinical information systems teams. Oversees enterprise reporting, Power BI dashboards, predictive analytics, AI-enabled solutions, Meditech Expanse optimization, data governance, and clinical system integrations. Manages supervisors and technical staff, prioritizes work, supports digital transformation, and partners with clinical, operational, financial, and executive stakeholders to improve decision-making, system adoption, and organizational performance.

Leads counterparty credit risk analytics, regulatory and management reporting, dashboards, risk indicators, data governance, and reporting framework development. Provides expert guidance on exposure metrics, derivatives, collateral, netting, stress testing, and regulatory requirements. Manages strategic initiatives, stakeholder relationships, audits, controls, operational processes, and team performance while delivering accurate risk insights and reporting solutions.

Leads counterparty credit risk analytics, exposure measurement, model governance, regulatory and stress testing deliverables, data controls, automation, and team leadership. Provides insights on PFE, settlement, MTM, CVA, collateral, netting, wrong-way risk, and trading exposures while partnering with risk, trading, model validation, and technology teams.

Leads CIBC’s media analytics and decision sciences practice, guiding measurement, experimentation, attribution, forecasting, optimization, and AI/ML initiatives. Partners with marketing and business leaders to translate priorities into actionable media insights and investment strategies. Oversees end-to-end analytical delivery, data quality, governance, and responsible AI practices while managing, mentoring, and developing a team of media analytics professionals. The role is hybrid, requiring 1–3 days per week onsite.

Build and maintain dbt analytics models, data quality tests, SQL transformations, semantic-layer metrics, and Omni BI dashboards for the Assurance business. Partner with stakeholders on arbitration risk, forecasting, product insights, and dealer-facing reporting. Independently scope and deliver analytical projects, respond to urgent questions, create self-service analytics capabilities, and communicate recommendations clearly to nontechnical audiences.

Drive regional sales of Axis security and network video solutions by building relationships with integrators, distributors, consultants, and end-users. Execute territory business plans, conduct site visits and product demonstrations, manage pipeline and forecasts in CRM, and participate in events and trainings to exceed sales targets.

Leads fraud analytics, customer risk scoring, fraud technology, intelligence, risk assessments, and prevention strategy across banking products and channels. Develops detection models, monitoring frameworks, dashboards, and executive reporting; manages vendors and governance activities; partners with risk, compliance, technology, data, and operations teams; and builds a high-performing fraud analytics and risk management team.

Leads CIBC’s Insurance Decision Science team, setting technical standards for actuarial, statistical, data science, and AI-enabled methods. Oversees analytics supporting insurance pricing, profitability, growth, forecasting, portfolio performance, and strategic decisions. Builds capabilities, challenges assumptions, advises executives, manages talent strategy, and develops relationships across insurance, retail banking, technology, and analytics teams.

Develop and enhance Workday reporting, automate HR data analysis, create reports and visualizations in Power BI, define metrics and dashboards, support data governance, advise HR leaders, and provide user training and change management. The role partners with stakeholders to solve complex HR data issues and enable data-driven decision-making.

Lead architecture and full-stack development for EASE, including TypeScript and Vue applications, backend APIs, automated testing, deployments, and production support across AWS and air-gapped on-premises environments. Own complex features, gather stakeholder feedback, improve performance and scalability, enhance CI/CD, and mentor engineers. The role also involves prototyping generative AI capabilities, integrating simulations, working with geospatial data, and maintaining secure, reliable distributed systems.

Develop and maintain Power BI dashboards, reports, DAX measures, KPIs, and dimensional data models for insurance stakeholders. Write complex SQL for data extraction, transformation, reconciliation, and analysis. Investigate data-quality issues, validate reporting accuracy, optimize performance, and translate insurance business requirements into actionable analytics solutions. Collaborate with engineering, business, and analytics teams across multiple data sources.

Own end-to-end business operations analytics for a core business area. Define business problems, metrics, reports, analyses, and experiments; surface insights; and drive decisions with product, growth, finance, and operations stakeholders. The role requires independent data analysis, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives across growth marketing, product, AI and automation, or strategic partnerships.

Own the analytical function for an embedded business unit across growth, product, AI, automation, or partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; make recommendations; and drive decisions and outcomes with cross-functional stakeholders. The role requires strong analytical ability, SQL or Python proficiency, first-principles problem solving, ownership of ambiguous initiatives, and persuasive communication.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate insights; communicate recommendations; and drive decisions and outcomes with cross-functional stakeholders. Requires strong analytical, problem-solving, communication, and ownership skills, with SQL or Python proficiency.

Own the analytical function for an embedded business unit across growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; communicate recommendations; influence stakeholders; and drive initiatives through execution. The role requires strong analytical judgment, independent data work, first-principles problem solving, and persuasive communication.

Own the discovery, direction, delivery, adoption, and continuous improvement of AI- and analytics-powered products for Commercial Banking. Translate business and user needs into product requirements, user stories, acceptance criteria, prioritized backlogs, and roadmaps. Partner with business leaders, data scientists, engineers, architects, and product teams to deliver measurable value, improve workflows, champion user experience, and align competing priorities.