Top Data Analyst Jobs in Calgary

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.

Own and govern Capital Power's end-to-end forward price curve framework: design, build, validate, and maintain curves; manage curve intake, configuration in ZEMA/Allegro, daily production monitoring, IPV, model validation, and governance reporting to senior committees.

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.

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.

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.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.

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.