Top Data Analyst Jobs in Montreal

Own audience analytics for major game franchises by analyzing player data, building clustering and segmentation models, identifying cross-game audience patterns, and delivering strategic recommendations. The role partners with marketing, production, CRM, media, finance, and research stakeholders, manages end-to-end analytical projects, tracks multiple workstreams, and communicates complex insights through compelling visualizations and presentations.

Analyzes insurance business data, develops and optimizes business intelligence tools, supports risk management and market analyses, defines KPIs, and improves data quality and governance. The role translates business needs into documented solutions and advises partners on data opportunities. It requires collaboration with pricing, claims, and business teams, along with proficiency in SQL and Power BI or Tableau.

Lead advanced analytics and data strategy for a live-service game, including telemetry systems, player behavior analysis, statistical modeling, dashboards, reporting, and data storytelling. Shape analytical best practices, mentor analysts, influence product and business decisions, and collaborate with multidisciplinary stakeholders on complex, high-impact challenges.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Supports public health data extraction, management, quality assurance, cleaning, validation, harmonization, documentation, and statistical analysis. Develops analytic datasets and performs qualitative, quantitative, and mixed-methods evaluations of program implementation and outcomes. Prepares technical memoranda, reports, tables, figures, and presentations, and communicates findings to program stakeholders. Requires knowledge of public health research, evaluation methods, government procedures, CDC administrative systems, and Microsoft Office.

Analyzes, validates, cleans, enriches, and maintains commercial real estate data. Conducts market research, monitors data quality, identifies trends, prepares reports and visualizations, and provides insights supporting leasing, investment, development, and client decisions. Collaborates with research, data, GIS, and technology teams across Canada to improve data platforms, workflows, and market intelligence capabilities.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Early-career data analyst supporting Manulife’s Data Office through data solutions, automation, AI-enabled applications, dashboards, pipelines, business analysis, and process improvement. The role involves translating business needs into requirements and scalable solutions, applying data governance, supporting testing and adoption, and collaborating with stakeholders across customer experience, analytics, and continuous improvement initiatives.

Analyze large datasets to produce dashboards, metrics, and insights supporting product, care, and business decisions. Build BI infrastructure, run A/B and multivariate tests, perform ad-hoc analyses and visualizations, and collaborate with stakeholders and data scientists to inform strategy and operations.

Lead marketing analytics and data strategy for B2B SaaS Marketing. Design measurement frameworks, own attribution, funnel and lifecycle analysis, forecasting, and marketing investment recommendations. Partner with senior marketing leaders and cross-functional teams to build data foundations, enable AI-assisted analytics, and mentor analysts to raise analytical standards.

Lead HR data capability delivery: translate business needs into functional specs and user stories, analyze HR/Workday data, design Workday reports, validate API integrations, triage data issues, and support testing and platform releases to enable workforce insights and AI-supported decisions.

Demonstrate ERP reporting capabilities, analyze customer requirements, design SQL- and Excel-based reporting solutions, develop proof-of-concepts and customer reports, provide initial product support, and train clients, partners, and colleagues. The role also requires creating documentation, estimating project scope, and maintaining expertise in Velixo and integrated ERP systems.

Owns advanced reporting, dashboards, data analysis, KPI development, ETL requirements, and data quality initiatives for internal stakeholders. The role delivers recurring and ad hoc reports, builds automated workflows, documents data definitions and processes, communicates insights to senior leaders, and supports BI sprint planning. Strong SQL, data visualization, stakeholder communication, and systematic data quality problem-solving are required.

Analyze and consolidate data from multiple systems, build scalable dashboards and executive reporting, define standardized metrics, ensure data quality, and translate complex datasets into actionable business insights. Partner cross-functionally with Sales, Marketing, Customer Success, Product, Finance, Operations, and Data Engineering to support decision-making and improve reporting processes.

Design, build and maintain robust Databricks data pipelines and ETL processes on cloud (Data Lake/Lakehouse). Develop transformations in Python and Spark, apply data quality best practices, integrate CI/CD (Azure DevOps), document solutions, and participate in Agile rituals to support analytical platforms and decision-making.

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.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.

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.

Analyze go-to-market performance across marketing, sales, revenue operations, and finance. Build reporting connecting campaigns to pipeline and revenue, investigate funnel and attribution questions, support budget analysis and planning, improve data quality, and communicate insights to technical and non-technical stakeholders. Collaborate with AI and Data Engineering teams on marketing data agents, architecture, and source tables.

Analyze high-volume data, develop tracking methods and frameworks with engineers, create visualizations, identify trends, and generate statistical insights to support business decisions. The role also involves prototyping solutions, understanding player behavior, and communicating findings in a dynamic gaming environment.

The Product Data Analyst will analyze operational data, develop analytics frameworks, create dashboards in Tableau, ensure data integrity, and collaborate across teams to enhance decision-making and reporting.

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.

Drive product and performance analytics for mobile app user acquisition: define core metrics, analyze campaign and product trends, build dashboards and data pipelines, support experiments and ML teams, automate reporting (including AI-powered workflows), and communicate findings and recommendations to stakeholders.

Lead exploratory analysis of player behaviour, build dashboards and visualizations, partner with designers/UX/engineers, translate analytical needs into pipeline requirements, maintain AI-powered tooling, monitor KPIs, and surface actionable insights to guide game design.