Top Analytics Jobs in Montreal

Lead revenue analytics by developing business cases, dashboards, KPIs, experiments, and automated analytics solutions. Partner with Client Success, Marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and identify growth opportunities. The role requires translating structured and unstructured data into actionable insights, standardizing analytical workflows, and communicating recommendations to internal and external stakeholders.

Lead and develop five experienced analysts and data scientists while personally owning analytics across ecommerce, health, and supply chain. Partner with executives, establish KPI and reporting standards, prioritize the analytics roadmap, deliver strategic insights, and advance AI-native self-service analytics tools. The role combines people leadership, hands-on analysis, data governance, and business strategy in a remote-first environment.

Leads cross-functional marketing analytics, performance measurement, AI deployment, initiative planning, and data governance. Performs hands-on analysis using SQL, Power BI, Databricks, CRM, campaign, and client data; develops measurement frameworks and presents decision-ready insights to executives. Owns AI agent rollout, guardrails, adoption, value tracking, and collaboration with IT and enterprise data governance. Requires influencing stakeholders across functions, managing portfolios, and connecting analytics to business outcomes.

Analyzes pipeline, funnel conversion, campaign performance, retention, and revenue drivers across Sales, Marketing, and Client Success. Builds and maintains dbt models, data marts, quality controls, documentation, and BI-as-code assets using Salesforce and modern data-stack technologies. Partners with stakeholders to turn ambiguous questions into decisions and advances AI-agent workflows for faster analytics and reporting.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface insights; make recommendations; and drive decisions and execution with cross-functional leaders. The role requires strong independent analytical skills, first-principles problem solving, persuasive communication, and ownership of ambiguous, high-impact initiatives.

Manage actuarial claims data analytics teams supporting claims profitability, customer experience, operational efficiency, and financial performance. Analyze actuarial reports, provide recommendations, advise claims operations, oversee technical studies, coach team members, allocate resources, and represent the actuarial service with stakeholders. Roles focus on casualty and legal, accident benefits, large loss, and specialty lines across Canada.

Owns marketing analytics measurement across campaigns, channels, attribution, funnel performance, and pipeline forecasting. Builds dashboards, attribution models, AI-powered scoring and insight tools, and executive-level analyses to guide marketing investment. Partners with Marketing Operations, Demand Generation, Events, Sales Operations, Finance, Security, Legal, and Data Engineering. Oversees marketing data quality, develops responsible AI practices, mentors analysts, and supports planning, budgeting, and ROI decisions.

Analyze large datasets to identify money-laundering and terrorist-financing patterns, improve AML detection and risk-scoring models, minimize false positives, build dashboards, and communicate trends and performance to AML leadership. The role partners with product, technology, and compliance teams to support data-driven financial crime prevention decisions.

Manage multiple market research projects across their lifecycle, including scripting quality control, fieldwork coordination, data table and analysis planning, coding oversight, basic statistical analysis, and report development. The role requires strong organization, communication, critical thinking, attention to detail, bilingual English/French fluency, and proficiency with Microsoft Office. It is fully remote for candidates in the Greater Montreal Area, with periodic local in-person events.

Develop analytical solutions with business partners, assess stakeholder needs, guide the Data and Analytics roadmap, and provide expertise on analytical methodologies, tools, and modeling. The role supports data-driven decision-making across investment operations and requires financial modeling, investment and risk management knowledge, strong communication skills, and bilingual English-French proficiency.

Analyzes marketing data to measure campaign impact across acquisition, retention, engagement, and conversion. Defines success metrics, benchmarks performance, develops experiments, evaluates paid media and creator campaigns, and delivers actionable insights and optimization recommendations. Builds reporting and analytics solutions using multiple data sources and collaborates with marketing, brand, data science, and cross-functional stakeholders to support data-driven strategy and budget planning.

Analyzes marketing and business data to measure campaign impact across paid media, creator campaigns, CRM, social, and digital channels. Develops KPIs, benchmarks, dashboards, analytical processes, and marketing experiments; identifies trends and opportunities across audiences and player segments; communicates insights and optimization recommendations to cross-functional stakeholders; supports predictive analysis and campaign budget planning.

Consult on data collection and analytics: gather client requirements, configure GA4/GTM (including server-side), build dashboards and automations, develop SQL/scripts, advise clients, train teams, and support sales estimations.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Perform hands-on product and player analytics across onboarding, retention, monetization, progression and LiveOps. Build and QA ETL pipelines in an AWS analytics stack, write cost- and performance-aware SQL, support A/B testing, and create reusable AI-enabled analytical workflows and notebooks to inform product, marketing, and LiveOps decisions.