Top Data Jobs in Ottawa

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Review and analyze news content from patient advocacy groups, extract insights, and input data into Zebricks to support AI/ML processes. Collaborate with the team on data projects, shape data best practices, and perform web research and spreadsheet-based data work.

Lead the design and development of a data platform, integrating data sources, driving architecture migration, and ensuring robust data governance and API development.

Design, build, and maintain scalable Databricks-based ETL/ELT pipelines and data models optimized for AI/ML. Manage orchestration, data quality, governance, and CI/CD (ADO → GitHub) while collaborating with cross-functional teams in Agile delivery.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Lead the Data Modeling team, focusing on the development of reusable core data models and metrics. Collaborate with various teams to ensure data quality and reliability in analytics and AI/ML. Hands-on role requiring experience in data modeling, SQL, Python, and Spark.

As a Senior Data Analyst, you will support Finance and Payments teams by building SQL/dbt models, creating Looker dashboards, and providing actionable financial insights.

As a Data Architect, you will architect data solutions, ensure data integrity, collaborate with stakeholders, and mentor junior team members, driving data value and management strategies.

Design and deliver enterprise-scale EDW and BI solutions, ensuring performance and scalability, while mentoring teams and engaging stakeholders.

Perform product analytics by analyzing large datasets, running A/B tests, building dashboards, applying statistical methods and ML for forecasting and segmentation, and communicating insights to product, sales, and customers to drive adoption and product improvements.

Lead and manage client data and digital strategy projects end-to-end: plan and run projects, produce C-level deliverables, coach and evaluate teams, perform advanced data analysis, define client needs, pitch solutions, and develop business proposals to grow accounts.

The Engineering Manager will lead cross-functional teams of engineers, focusing on building high-performing environments, managing technical delivery, fostering team growth, and ensuring data-driven strategies.

Lead and develop a team to govern and validate clinical data builds, vendor deliverables, and data integrations. Implement and maintain CDASH/SDTM/ADaM standards, validation libraries, and submission-ready processes. Oversee data ingestion into the Clinical Data Warehouse, drive automation (SAS, Python, AI), maintain SOPs/QMS, and partner with Biostatistics, Data Management, Standards, and CROs to ensure high-quality, analysis-ready datasets.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

Deliver front-office investment technology consulting: requirements, workflow design, system configuration, integration, testing, and handover. Provide subject-matter expertise on OMS/EMS/PMS platforms, data architecture, cloud integrations, and program governance to ensure timely, on-budget transformations.

Lead data-driven underwriting improvements by analyzing claims, risk signals, and underwriting data; build statistical and ML models for cyber risk assessment, pricing, and automation; produce dashboards and reports; collaborate with actuarial, product, and engineering teams; mentor teammates and lead cross-functional initiatives to optimize underwriting and risk selection.

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.

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.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Lead end-to-end debit analytics: design and modernize reporting, build executive dashboards, run A/B tests, produce actionable insights, optimize measurement/KPIs, mentor analysts, and partner with stakeholders to influence product and business decisions using cloud data platforms and advanced SQL/Python analytics.

Lead labeling quality and methodology for ML at Coalition: design annotation tasks, define quality frameworks (IAA, gold standards), manage Label Studio and vendor BPOs, partner with ML/data teams, and track operational metrics to improve accuracy and throughput.

Design and build data models, pipelines, and ML systems for production. Integrate Snowflake/AWS with Salesforce Data Cloud, deploy and monitor models (MLOps), and deliver data products and dashboards to enable AI-driven automation across the platform.

Lead data management for clinical trials including database setup, eCRF specification, validation/edit checks, testing, data review/reconciliation, SAE reconciliation, database lock/unlock, vendor data transfers, training, and DM documentation to meet timelines and quality standards.