Top Data Analyst Jobs in Vancouver

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

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.

Serve as delivery lead and senior digital analyst for clients: gather measurement requirements, analyze large event datasets (BigQuery/SQL), build visualizations, present insights, guide implementations (GTM/Tag tools), coordinate cross-functional delivery, and ensure QA and on-time execution.

The Robot Data Operations Analyst will control robots, evaluate performance, provide quality assurance, and document observations safely in an R&D setting.

The Data Analyst will support business needs through technical problem-solving and data analysis, focusing on improving user experience and conversion rates in a B2B2C environment.

Support the Financial Data product by translating roadmap goals into engineering requirements, creating mockups and business logic, querying PostgreSQL/Snowflake/Athena for data insights, performing data validation and QA, documenting product features, coordinating cross-team prioritization, and contributing to release communications.

Lead subscription analytics: define KPIs, design experiments (A/B tests), analyze customer lifecycle, identify retention/growth opportunities, ensure data quality, and build dashboards to inform cross-functional decisions.

Ensure quality, consistency, and governance of enterprise master data through data analysis, reporting, and collaboration. Perform data mining, identify quality issues, develop dashboards, run system queries, maintain data, support supplier outreach, and meet SLAs while supporting business initiatives and process improvements.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

Lead product analytics by building scalable data models and measurement frameworks, owning dbt workflows, performing cohort/retention and funnel analyses, defining KPIs, automating analytics, and presenting recommendations to influence product and business decisions.

Own and maintain core financial datasets and dbt models; write complex SQL; build and optimize Looker dashboards; troubleshoot data quality; and deliver reconciled, actionable financial insights to Finance and Payments stakeholders.

Design and build audit-ready data architecture and ETL pipelines, maintain inventories/playbooks/catalogs for audit, implement automated validation and monitoring, assess change impacts, and translate audit requirements into technical specifications for stakeholders.

The Senior Data Quality Analyst will analyze and improve data quality across systems, collaborate on data governance, and ensure accurate data processes, contributing to actionable recommendations and stakeholder communication.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Embed within product teams to deliver actionable analytics: build dashboards, run deep-dive analyses, translate ambiguous business questions into data solutions, drive product growth, automate reporting, ensure analytics quality, and communicate insights to stakeholders to influence product decisions and forecasting.

Research, evaluate, and manage partnerships with data providers. Assess datasets for coverage and interoperability, support deal structuring, maintain partnership pipeline, and collaborate with product, engineering, and legal to integrate data into the platform.

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.