Top Data Analytics Jobs in Toronto

Produce and distribute business reports, conduct ad-hoc data mining, maintain data quality and documentation, steward asset management data, support schema changes and system testing, influence data-service roadmaps, and apply predictive and prescriptive analytics. Lead research and experimentation within the AI product roadmap while translating complex insights into actionable recommendations for stakeholders.

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.

Serves as the Services PLM liaison to Supply Chain, translating supply-chain costs, operating models, capabilities, and constraints into business cases, portfolio recommendations, pricing inputs, and investment decisions. Develops cost models and P&Ls, coordinates cross-functional change requests, tracks implementation plans and risks, monitors operating performance, and supports staging, integration, repair, spares, logistics, and circular-economy services.

Leads a business analytics team responsible for long-term revenue and customer demand forecasting, capacity planning, workforce scenarios, and strategic modeling. Builds integrated forecasting, sensitivity, and scenario models; establishes governance, validation, and backtesting standards; and translates analytics into hiring, training, investment, and operational recommendations. Partners with Care, Finance, Operations, Recruiting, and senior executives to assess risks, tradeoffs, and business outcomes.

Drives sales and business development for process analytics products across a bioprocessing territory. Builds relationships with biopharmaceutical companies, research institutions, and contract manufacturing organizations; develops sales strategies; analyzes markets and competitors; collaborates with technical and commercial teams; provides customer training; and manages CRM, forecasts, reports, Tableau, and Power BI data. Requires extensive regional travel and expertise in bioprocessing, biotechnology, PAT, and spectroscopy.

Administer SKAN AI and ProHance platforms, develop Power BI dashboards and automated reporting, analyze operational and workforce data, and identify process improvement opportunities. The role supports process intelligence, productivity analysis, workflow automation, system integrations, business application development, and data-driven recommendations. Responsibilities also include stakeholder engagement, user training, documentation, governance, platform maintenance, and translating business requirements into scalable analytics and process optimization solutions.

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.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Own end-to-end digital media campaigns across DV360, CM360, YouTube, Meta, and TikTok. Responsibilities include campaign setup, trafficking, QA, tracking, Floodlight implementation, pacing, programmatic optimization, PMP and audience activation, reporting, testing, and client recommendations. The role requires troubleshooting tracking issues, analyzing performance data, automating reports, and collaborating with internal teams and publishers. It is fully remote across the U.S. and Canada, with occasional travel for company events.

Build and maintain trusted analytical datasets, data marts, semantic models, certified metrics, and reusable data products. Develop scalable ELT transformations, data quality controls, testing, and governed business logic that support enterprise reporting, business intelligence, advanced analytics, and AI initiatives. Partner with technical and business teams, guide design practices, mentor colleagues, and translate requirements into reliable data solutions.

Lead Securian Canada’s enterprise analytics strategy, business intelligence, analytics engineering, and AI initiatives. Build scalable data products, KPI frameworks, semantic models, dashboards, and decision-support solutions. Advise executives, translate complex business challenges into actionable insights, establish responsible AI and data governance practices, and lead a multidisciplinary team while developing talent and fostering data-informed decision-making across the organization.

Develops fraud detection, prevention, and investigation models using statistical analysis, machine learning, deep learning, and large-scale data processing. Responsibilities include collecting and integrating structured and unstructured data, identifying financial crime patterns, developing predictive solutions, monitoring model performance, resolving analytical issues, and communicating insights to stakeholders. The role also supports data and AI tool development, training, and innovation across the Financial Crimes Unit.

Owns a defined territory and manages the full B2B software sales cycle from prospecting through close. Responsibilities include acquiring and expanding accounts, conducting consultative discovery, presenting ROI-focused business cases, negotiating, forecasting, maintaining CRM data, developing territory plans, and building executive relationships across manufacturing and operational functions. The role requires quota achievement, complex multi-stakeholder sales experience, and 20–35% travel in the greater Toronto area.

Sell Salesforce Data solutions to Canadian federal government agencies in Ottawa. Responsibilities include developing territory plans, building pipeline, managing public-sector accounts, identifying expansion opportunities, explaining data solutions to business and technical stakeholders, collaborating with partners and internal teams, addressing client issues, and reporting business progress. The role requires extensive enterprise technology sales experience, preferably with data platforms and Canadian public-sector clients.

Manage relationships with enterprise customers, serving as the primary liaison and driving retention, renewals, pricing discussions, revenue growth, forecasting, and upsell opportunities. Develop strategic account plans, conduct executive-level quarterly business reviews, analyze account performance, and collaborate with internal teams to deliver strong customer outcomes. The role requires regular customer-site travel, Salesforce use, and enterprise account management experience.

Leads advanced statistical modeling and analytics using retail, customer, and loyalty data. Develops forecasting, causal inference, experimentation, predictive modeling, segmentation, optimization, and statistical learning solutions. Partners with senior leaders to improve customer growth, retention, promotions, and financial performance. Establishes model validation and monitoring standards, translates quantitative findings into recommendations, and coaches analysts and data scientists while guiding modeling and experimentation strategy.

Lead wind energy assessments and performance analyses for utility-scale renewable projects. Analyze SCADA, meteorological, geospatial, and operational datasets; develop Python, MATLAB, or R tools and automated workflows; evaluate energy production, uncertainty, losses, and risks; provide technical consulting, peer review, customer support, and mentoring; and advance AI, data management, visualization, and analytical methodologies.

Leads advanced statistical modeling and analytics using retail, customer, and loyalty data. Develops forecasting, causal inference, experimentation, predictive modeling, segmentation, optimization, and statistical learning solutions. Partners with senior leaders to drive customer growth, retention, promotional effectiveness, and financial performance. Establishes model validation and monitoring standards, translates complex analyses into recommendations, and coaches analysts and data scientists while maintaining technical oversight.

Generate and nurture pipeline through high-touch outbound and inbound activities: segment CRM cohorts, write personalized outreach, use AI tools to create assets, qualify intent to SAL criteria, book meetings, and feed conversion insights back to improve targeting.

Build and own core infrastructure for Motion’s AI agent runtime, including its virtual machine, internal services, integrations, and platform primitives. Develop end-to-end features using TypeScript, Node.js, Rust, and related technologies while ensuring systems are fast, reliable, secure, and scalable. Collaborate on a small, high-ownership team, make architectural decisions, translate technical issues into business impact, and use AI-assisted coding while maintaining strong engineering standards.

Leads strategy and execution for large-scale data engineering and analytics programs. Coordinates engineering, data science, product, and business stakeholders; manages roadmaps, dependencies, milestones, risks, reporting, and delivery. Ensures data definitions, transformations, models, and downstream analytics remain accurate and fit for purpose while navigating complex, ambiguous initiatives involving multiple teams and partners.

Lead end-to-end delivery of enterprise Generative AI and Agentic AI programs, coordinating data science, machine learning, data engineering, product, architecture, and client teams. Oversee RAG pipelines, multi-agent ecosystems, knowledge graphs, production deployment, risks, dependencies, and technical challenges. Communicate program progress, blockers, and decisions to senior leadership and stakeholders while ensuring successful delivery of complex AI initiatives.

Manages technology procurement, strategic sourcing, vendor negotiations, renewals, contracts, and commercial risk. Develops procurement analytics using spend, usage, contract, and vendor data, including Excel and Power BI dashboards. Supports cloud, SaaS, marketplace, AI, and Azure purchasing decisions through forecasting, consumption analysis, cost optimization, and commercial recommendations. Collaborates with IT, Security, Finance, Legal, and business stakeholders to deliver savings, cost avoidance, governance, and improved contract terms.

Own retention, renewals, expansion, onboarding, and strategic outcomes for 10–30 enterprise customer accounts. Build executive relationships, lead complex change management, develop account plans, identify creative strategy gaps, conduct executive business reviews, and provide customer feedback to Product and Leadership. Use Motion and its AI agent, Runneth, to improve creative testing workflows and customer impact.

Own the strategy, roadmap, and delivery of Coalition’s scanning and cyber-risk data products. Partner with Engineering, Data, Security, Underwriting, Actuarial, Design, and customer teams to improve asset discovery, data quality, accuracy, reliability, scalability, and usability. Define metrics, prioritize initiatives, translate technical challenges into product requirements, guide discovery through launch, and develop APIs and experiences that help stakeholders understand and act on cyber-risk intelligence.