Top Analyst Jobs in Toronto

Lead requirements gathering, perform market research, produce BRDs/FRDs/use cases, support development and testing (UAT), train users, mentor others, and drive digital banking product implementations across multiple projects.

Partner with Sales, Marketing, and Customer Success to lead GTM FP&A: forecasting, headcount and Opex management, bookings/ARR metrics, quota and pipeline modeling, ROI/unit-economics analysis, compensation modeling, automation and AI-driven reporting, and board-level reporting. Build scalable analytics, AI-powered workflows, and drive monthly/quarterly planning and business reviews.

Manage land project workflows, delegate tasks, track timelines and deliverables, liaise with clients and teams, ensure regulatory compliance for land acquisitions and permits, audit documentation, prepare client reports and tracking tools, and train team members to maintain quality and best practices.

Own marketing tracking and measurement across 14 markets, implement and audit GTM/GA4/pixels/server-side tracking, build automated Looker dashboards, run incrementality and A/B/geo-lift tests, define budget allocation frameworks, and set analytics standards and documentation to inform media spend decisions.

Support Grafana's AI organization by defining KPIs, designing experiments, guiding instrumentation, building dbt models, creating dashboards, and translating analytics into product recommendations to improve AI-powered features and workflows.

Serve as a strategic FP&A partner owning planning, forecasting, budgeting, and performance management. Build models, deliver executive dashboards, analyze margin and spend trends, support pricing/contract decisions, lead financial reviews, and drive cross-functional initiatives to optimize profitability and working capital.

Support month-end and quarter-end GAAP close, prepare management reports and reconciliations, investigate variances, prepare journal entries, liaise with Shared Services, and drive process improvements and internal control compliance.

Provide business analysis for complex IT initiatives: gather and manage requirements, create diagrams and user stories, conduct process reengineering, support solution design, lead stakeholder workshops, and contribute to digital transformation and performance measurement.

As a Power Markets Analyst, you'll provide market analytics, insights, and collaborate with engineering and policy teams to optimize performance in established electricity markets.

Provide front-line, multi-channel client support and manage full lifecycle inquiries; assist onboarding and API integrations; test application/APIs, create user and API documentation, and lead process improvement and automation efforts while working cross-functionally.

Support property underwriting by evaluating and rating risks, assisting CAT modeling, entering new and renewal account data, preparing renewal documentation, participating in self-audits, and responding to brokers to maintain compliance and efficient workflows.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

The Organic Growth Analyst will support SEO and content strategies for B2B SaaS clients, conduct analyses, and help track performance.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

Lead SAP EWM outbound process design and implementation: gather requirements, identify gaps, produce functional RICEFW designs, run workshops, prepare training documentation, and support end-to-end SAP S/4HANA EWM deployments. Prioritize candidates with food manufacturing experience and bilingual (English/French) skills.

Lead requirements-gathering, analyze and document processes, develop business cases, create specifications, and support IT solutions while ensuring stakeholder alignment.

Partner with multinational clients to gather requirements, define KPIs, develop business cases, and oversee GRAVTY® loyalty program implementations. Provide product expertise, deliver client training, manage project documentation and SLAs, collaborate with product management on features, and create product marketing collaterals to support go-to-market strategies.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

The Customer Engagement Analyst role involves configuring the unitQ platform, conducting analyses, building customer-facing artifacts, and collaborating with teams to address customer needs.

The Analyst supports template configuration, documentation, testing, and deployment activities. They assist in maintaining data accuracy and follow established standards, while learning ERP processes and enterprise application fundamentals.

Lead and build the Customer Experience analytics function, owning CX data strategy, BI, forecasting, capacity planning, operational analytics, and executive reporting. Translate large datasets into actionable insights, predictive models, and staffing forecasts, measure AI and human interactions, identify journey inefficiencies, and quantify CX impact on revenue while partnering with CX, Finance, and Data teams.

Audit and ensure quality of data labeling outputs, coach and onboard Data Labeling Associates, provide actionable feedback, monitor workflows, identify patterns and edge cases, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and review data labeling outputs, provide actionable feedback, train and support labeling teams, monitor workflows, identify recurring issues and edge cases, participate in calibrations and stakeholder syncs, and help improve guidelines and processes in human-in-the-loop AI workflows.

Audit and ensure quality of labeled data by reviewing DLA outputs, providing feedback and coaching, supporting onboarding and training, monitoring workflows, identifying recurring issues and edge cases, and contributing to guideline and process improvements in human-in-the-loop AI workflows.

Audit and improve data labeling quality in human-in-the-loop ML workflows. Coach and onboard labelers, provide actionable feedback, monitor queues, identify recurring issues, and help refine guidelines and processes.