Top Data Jobs in Ottawa

Embedded on a core business team, the Associate Data Scientist defines questions, builds metrics/reports, runs analyses and experiments, surfaces insights, and drives data-informed recommendations end-to-end to impact product, growth, AI/automation, or partnerships.

Embedded in a core business area, you'll define problems, build analyses, metrics, reports and experiments, surface insights, and drive data-informed product, growth, AI, or partnerships outcomes end-to-end.

Embedded data scientist owning analytics for a core business area: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end.

Embedded on a core business unit, you will define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a business unit to define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

Embedded within a core business area, you will define the right problems, design metrics and experiments, pull and analyze data, build reports, and surface insights. You will make recommendations, secure stakeholder buy-in, and drive execution to improve product, growth, automation, or partnership outcomes.

Lead and advise on data architecture and datastore designs, ensuring scalability and reliability, while managing cross-application projects and influencing technical decisions.

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

Design and lead enterprise data architecture for agentic AI, including hybrid lakehouse and graph/vector integrations. Define schemas and knowledge graphs, ensure database performance and governance across Snowflake/Kinetica/BigQuery, establish ETL/ELT and CDC/streaming strategies, and act as technical client lead for architecture, security, and performance benchmarks.

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

Lead Life360's Data Engineering organization and own end-to-end data platform and analytics engineering strategy. Define architecture for ingestion, transformation, modeling, and serving data for humans and LLMs. Manage engineering managers and teams, drive self-serve data capabilities, cost management, vendor decisions, data quality/governance, and partner cross-functionally to prioritize engineering work that drives business impact.

The Senior Geo Data Scientist will develop advanced machine learning models for geospatial data, build scalable data pipelines, and enhance model performance for mineral exploration.

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 and develop a team of analysts, manage analytics projects, establish methodologies, and enhance reporting and automation processes.

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

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.

Lead the PoC data science team, delivering POCs for enterprise clients, mentoring team members, and driving fraud analytics and ML solutions.

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.

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.

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

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.