Top Data Analytics Jobs in Toronto

Leads Autodesk’s enterprise GTM revenue analytics foundation, including KPI governance, semantic data models, reporting standards, dashboards, and executive insights. Partners with data, systems, finance, sales, marketing, and customer success teams to improve revenue decision-making. Defines AI-enabled analytics use cases and roadmap while ensuring scalable, secure, governed solutions. Serves as a technical and analytical leader, influencing cross-functional priorities and mentoring team members.

Leads clinical-program analytics and performance improvement initiatives, translating data into measurable gains in quality, outcomes, access, efficiency, and resource stewardship. Builds enterprise capabilities in continuous improvement, performance management, analytics, and change leadership through systems, training, coaching, and mentorship. Oversees and develops a high-performing team while fostering accountability, collaboration, innovation, and sustainable organizational improvement.

Lead and grow a team of analytics engineers to build an AI-ready, centralized data foundation. Hands-on duties include writing/reviewing SQL and dbt, designing semantic and dimensional data models, driving data quality, observability, testing, and CI/CD, partnering cross-functionally to deliver scalable data products, and recruiting and developing engineering talent.

Leads Sales and Marketing Analytics by managing analysts, setting the analytics roadmap, and guiding measurement strategy across acquisition, demand generation, sales, partnerships, and revenue funnels. Owns frameworks for attribution, incrementality, forecasting, marketing mix modeling, CAC, LTV, and ROI. Partners with senior leaders and data teams to deliver trusted reporting, executive insights, self-serve analytics, automation, and responsible AI-powered decision support.

Own full sales cycle for Southern California enterprise accounts: source and close new logos, build executive relationships, run ROI-driven POCs, collaborate with Sales Engineering, and meet ARR targets through repeatable, metric-based sales strategies.

Partner with prospective and existing customers to lead technical discovery, design integrations and proofs of concept, run tailored demos, troubleshoot implementation issues, and translate customer feedback into product requirements while collaborating closely with sales, product, engineering, and customer success.

The Principal Product Manager will define product vision, roadmap, and strategy, ensuring operational excellence while delivering exceptional customer experience and measurable outcomes through cross-functional collaboration.

Lead operational execution of eDiscovery workflows from intake through production and case closure. Manage collections, processing, hosting, Relativity workspaces, review/analytics, vendor relationships, QA, and billing to ensure efficient, defensible discovery support for litigation teams.

The Account Manager will manage client and talent relationships, oversee partnerships, develop content strategies, and ensure successful project outcomes with a focus on the creator economy.

Design and lead Genesys Cloud CX contact center architectures, translate business requirements into scalable secure solutions, oversee integrations (CRM, WFM, analytics), ensure performance, compliance, and mentor engineering teams to deliver cloud-based CX platforms.

Build and own the analytics foundation: maintain dbt models and Snowflake, create ELT pipelines (Python/Airflow), design semantic layers, ensure data quality and reconciliation, enable self-serve analytics and measurement for cross-functional teams, and support AI-ready data infrastructure.

Lead end-to-end implementations for mid-market and smaller enterprise customers, managing ~15 concurrent 4–8 week SaaS onboarding projects. Develop and execute implementation plans, align stakeholders, configure multi-module systems, drive change management, advise on best practices, and collaborate across CS, Sales, Product, Engineering, and Ops to ensure rapid time-to-value and strong customer outcomes.

Lead North's integrations strategy and execution: prioritize, ship, and drive adoption of connectors and ecosystem tooling. Partner with customers and engineering to convert integrations into reusable platform capabilities (auth, connector framework, data sync, permissions). Define developer/partner experience (APIs, SDKs, plugins) and instrument analytics to measure adoption, time-to-stand-up, and retention.

Manage multiple marketing research projects from fieldwork through final reporting. Responsibilities include scripting quality control, fieldwork coordination, note-taking, data table and analysis planning, overseeing data setup and coding, basic statistical analysis, and report development. The role requires strong communication, organization, attention to detail, independent time management, and proficiency with Microsoft Office. It is fully remote but limited primarily to candidates in the Greater Toronto Area.

Prepares and maintains institutional client reports, performance measurements, portfolio return calculations, and investment attribution analyses. Investigates data discrepancies, resolves reporting issues, supports UAT testing, and ensures timely, accurate deliverables under service-level and risk standards. The role also identifies process improvements, automates workflows, interprets large datasets, and communicates concise insights to senior staff. Employees work onsite four days per week.

Build and productionize AI agents for product analytics, integrating LLMs, tools, retrieval pipelines, and data systems. Develop data pipelines, evaluation frameworks, guardrails, telemetry, and monitoring. Diagnose agent quality issues, improve prompts and context, and contribute to proactive product intelligence systems. Collaborate with product and engineering teams to translate business needs into reliable agent designs while documenting work and following shared development standards.

Develop end-to-end AI and machine learning solutions for Global Asset Management and Wealth Management using structured and unstructured data. Apply statistics, NLP, GenAI, optimization, and advanced modeling techniques; conduct research, engineer features, build APIs, and deploy scalable data products. Partner with business stakeholders to translate needs into insights, mentor junior scientists, and provide technical leadership. Work in a hybrid arrangement with two to three onsite days weekly in Toronto.

The Operational Excellence Senior Analyst will drive process improvements using Lean and Six Sigma, influence change, and facilitate cross-functional teams to enhance operational efficiency and performance metrics.

Lead ad-serving product roadmap and strategy to improve advertiser ROAS and budget utilization. Drive AI/ML and generative AI innovations, own technical requirements with engineering and analytics, run experiments and A/B tests, align roadmaps with commercial and finance teams, represent product to senior leadership, and ensure timely execution with program and operations partners.

Lead roadmap and execution for ad-serving, bidding, targeting, auction mechanics, and core marketplace infrastructure. Apply AI/ML and generative models to improve ROAS, budget utilization, and advertiser outcomes, partnering with engineering, analytics, commercial, finance, and legal. Drive experimentation, A/B testing, and data-driven product decisions.

Lead product design for Stripe's Data & AI products, shaping systems and new products from ambiguous strategic problems to detailed interaction design. Collaborate cross-functionally with PMs, engineers, and design leaders to build trust-focused, end-to-end experiences and design systems.

Hands-on director-level product designer for enterprise SaaS who owns the design system, user psychology, dashboards, data visualizations, and habit-forming product mechanics. Designs workflows to drive adoption, retention, referrals, and expansion while partnering with Product, Engineering, Sales, and Customer Success. Prototypes, tests, and refines UX based on analytics and A/B experiments to align design with revenue metrics.

Senior pre-sales engineer partnering with sales and channel partners to run technical demos, lead POCs, design solutions, and close large deals. Present to executives and technical audiences, build cloud ML/generative AI solutions, and advise on data architecture and Snowflake positioning.

Own the vision, roadmap, and delivery of AI and analytics capabilities for an enterprise EHSQ SaaS platform. Lead customer and market discovery, prioritize backlogs, define product metrics, and partner with engineering, data science, architecture, design, sales, marketing, and services teams. Drive AI feature launches, adoption measurement, governance, enablement, pricing, and executive communications while ensuring trustworthy, explainable, and compliant product experiences.

Designs and deploys enterprise knowledge graph solutions, semantic models, ontologies, taxonomies, and data governance frameworks. Establishes metadata management, lineage, business glossaries, stewardship workflows, and data quality standards. Collaborates with business, AI/ML, and engineering teams to translate domains into scalable architectures and integrate graphs with data fabrics, data meshes, and AI systems. Serves as a technical authority on client deployments and converts ambiguous requirements into production-ready data architecture blueprints.