Top Data Jobs in Ottawa

Lead vision, roadmap, and hands-on delivery of a secure AI, GenAI, and data platform in AWS. Implement Amazon Bedrock and SageMaker powered GenAI and MLOps capabilities, establish secure data foundations, define guardrails/compliance automation, own platform reliability and onboarding, and drive cross-functional adoption and governance for regulated environments.

Collect and record pedestrian counts at designated intersections during AM and PM shifts in September/October 2026. Follow protocols, use a smartphone for data entry, work outdoors in varied weather, maintain safety and professionalism, and report to the Program Manager for School Zone Safety.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

This role involves outbound prospecting, conducting cold calls, emails, and LinkedIn outreach to qualify opportunities and set meetings in a remote capacity.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

The Engineering Manager will lead the data platform team, driving architectural decisions, optimizing systems for performance, and collaborating cross-functionally to enhance data usability and value.

The Senior Data Scientist will build models and analyses, design experiments, integrate datasets, and leverage AI for improved workflows and insights in data science.

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

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.

Senior data analyst/programmer using SAS or R to analyze commercial claims and EHR real-world data. Create longitudinal cohorts, derive baseline/outcome variables, assess data quality, apply epidemiologic study designs and statistical methods (regression, survival), review protocols/SAPs, and program TFLs. Familiarity with OMOP CDM and OHDSI tools is a plus; prior pharmaceutical experience preferred.

Lead and coordinate client legacy data integration into TELUS Health systems. Oversee conversion tasks, ensure data quality, run workshops, identify gaps, propose process changes, escalate issues, prioritize conversion work, and report progress and risks to project management.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Lead and scale Scribd's Data & Analytics organization across Product Analytics, Data Science, and Analytics Engineering. Build operating model, data governance, experimentation frameworks, AI-native workflows, and infrastructure to accelerate insight delivery. Develop director-level leaders, recruit talent, and embed data-driven decision-making at the executive level to drive growth, retention, and portfolio-wide strategy.

Design and deploy predictive models and segmentations using statistical and ML/AI methods. Prepare, clean, and feature-engineer data from warehouses, develop and operationalize models, create visualizations and presentations, document rules, and advise stakeholders to inform business decisions and improve data management tools.

Build and maintain scalable, reliable data systems and pipelines, uphold SLOs, partner with Product/Sales/Finance, enable self-service analytics, contribute to data platform strategy, and improve engineering practices for testing, reliability, and documentation.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

The Senior Data Analyst will analyze player behavior, create dashboards, guide product growth with insights, and collaborate on A/B testing at Rovio.

As a Data Annotation Specialist, you will break down engineering tasks for AI models, evaluate their responses, and ensure outputs are accurate through labeling and proofreading.

As a Data Engineer, you'll design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Lead optimization and scaling of Snowflake architecture, build resilient ELT/ETL and MLOps pipelines, implement data observability, automate workflows with AI-assisted tools, and design enterprise semantic models to support analytics and commercial data products.

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.

As a Software Engineer 2 - Data Acquisition, you'll design and build data ingestion pipelines, ensuring quality and performance across multiple data domains while participating in code reviews and collaborating with data consumers.

Lead and grow a small data team while remaining hands-on in data engineering, analytics engineering, and infrastructure. Own data strategy, warehouse architecture, pipelines, modeling, and self-serve analytics. Partner cross-functionally to deliver trusted metrics, experimentation, and applied ML capabilities (search, recommendations, personalization). Drive adoption of data quality, documentation, self-service, and modern data practices.

Lead and execute end-to-end Salesforce data migration projects: define strategy, design and validate data models, build ETL pipelines, resolve data quality issues, perform reconciliation and validation, document mappings, and coordinate cross-functional teams to ensure compliant, accurate migrations on schedule.