Top Data Jobs in Ottawa

Intern will build enterprise data foundations and AI agents connecting LLMs to authoritative business knowledge. Responsibilities include developing retrieval/RAG pipelines, agent workflows, persistent memory/state management, governance controls, auditability, and integrations with vector DBs, knowledge graphs, enterprise tools, and multiple LLM providers.

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

Contributors record authentic first-person video of household tasks, hands-on work, and everyday activities using a phone mounted to a headstrap. They choose their own schedule, preferably recording at least 10 hours weekly, then upload footage through Perle’s app for review and payment. Contributors must be at least 18, reside in the United States, Canada, or Latin America, have a supported smartphone, and be comfortable wearing a headstrap.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

Design and optimize data pipelines, cleanse and transform datasets, and build reliable reporting and analytics solutions using PostgreSQL, Metabase, and related tools. Collaborate with stakeholders to define KPIs, develop dashboards, troubleshoot data processes, and deliver actionable insights that support data-driven decisions.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Lead design and implementation of a federated Lakehouse data platform, unify data silos, define governance/observability, enable secure AI/ML (RAG/vector readiness), mentor architects/engineers, and present roadmaps to executives.

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.

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.

The Data Engineer will analyze and interpret data to drive insights, create dashboards, and enhance product performance, collaborating with cross-functional teams.

As a Data Analyst, you will analyze user behavior and product performance, creating reports and dashboards to aid decision-making and optimize user experience.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

Lead enterprise Data & AI transformation initiatives, managing the delivery of cloud-based analytics platforms while aligning business and technology objectives. Responsibilities include program governance, stakeholder management, and overseeing implementations of Microsoft Fabric.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

The Director of Data Strategy will develop and execute a data strategy, ensuring data quality and governance across the organization, fostering collaboration among various departments for improved analytics and business outcomes.

Perform clinical data management for Phase I-IV studies: design and test eCRFs/EDC, develop edit checks and DMPs, manage queries, reconcile external data and SAEs, support database lock, and collaborate with cross-functional teams and vendors.

The Strategic Customer Representative drives growth within data centre construction sectors, manages client relationships, and coordinates projects with multiple stakeholders.

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.

The Senior Data Platform Engineer will design and operate a unified data platform, ensuring reliable data flows and collaborating across teams to shape data strategy and architecture.