Top Data Analyst Jobs in Ottawa

Perform systems analysis and options analysis for an Intelligence Mission Data project: gather and translate business requirements into system specifications, develop use cases, evaluate technical solutions, ensure integration with business processes, support testing, and prepare reports, briefings, and meeting artifacts for project stakeholders.

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

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.

Use advanced analytics to monitor collections performance, evaluate third-party agencies, design incentive programs, and develop Power BI dashboards. Partner with operations, strategy, and risk to translate insights into actions, document data flows, and deliver training to non-analytical users to improve collections efficiency and portfolio outcomes.

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.

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 ensure quality of data labeling outputs, coach and onboard annotators, enforce and improve guidelines, identify recurring issues and edge cases, escalate risks, and document feedback to support 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.

Audit and ensure quality of data labeling outputs, coach and onboard annotators, apply and refine guidelines, monitor workflows and escalate issues, document findings, and support human-in-the-loop AI evaluation processes.

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.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Audit and ensure quality of data labeling work for ML using human-in-the-loop processes. Provide feedback, train and support annotators, monitor workflows, identify recurring issues, and help improve guidelines and processes.