Top Data Jobs in Ottawa

Perform clinical review of oncology study participant-level data to ensure readiness for milestones (interim/final analysis, submissions). Conduct point-to-point and interpretive checks, generate and resolve queries, identify trends and safety signals, liaise with study team, and follow SOPs to maintain data quality and integrity.

Own and evolve ClickHouse's Python connectors and SDKs; build integrations with orchestration and transformation tools; design AI/LLM connector patterns for RAG, vector search, and feature pipelines; engage with open-source community; collaborate across product and engineering to prioritize and ship production-grade data integrations.

Design and analyze large-scale A/B and causal studies, build predictive and decision models, apply learning analytics and psychometric methods to measure learner outcomes, partner with product and engineering to instrument data and drive product decisions.

Remote Data Researcher responsible for conducting data research, designing and implementing surveys, performing data entry, analyzing datasets to identify trends, preparing reports and presentations, and collaborating with cross-functional teams to provide actionable recommendations.

The MDM Data Analyst will translate business needs into data requirements, document governance rules, and ensure high-quality master data management across enterprise systems.

Lead Kraken's Data Platform team focused on real-time infrastructure for data systems, managing team dynamics, architecture design, and promoting AI automation.

Lead design and implement a scalable Medallion lakehouse on GCS and Databricks. Build and govern ingestion and transformation pipelines (Astro/Airflow, PySpark, Delta Live Tables), apply domain-driven data modeling, manage Unity Catalog access and lineage, collaborate with analytics and vendors, and proactively surface risks with clear documentation.

The VP of Data & AI Engineering leads Duck Creek's enterprise data and AI strategy, overseeing global teams, implementing scalable platforms, and ensuring data governance and responsible AI practices.

Lead analytics for Internal Audit Claims: extract, transform, reconcile, and validate large claims datasets; build and maintain Power BI reports/dashboards; perform QA and tie-outs; support automation, bots/AI enablement, and executive reporting; mentor other analysts and partner with audit, IT, and business stakeholders to deliver repeatable, validated analytics.

The Software Engineer will provide technical support to customers, collaborate with engineering teams, and drive customer success initiatives while leveraging Python and SQL expertise.

Lead design and delivery of end-to-end ML solutions for insurance (claims, underwriting, sales). Own feature engineering, model selection, training, validation, and handling imbalanced/weak-label data. Ensure explainability, governance, and production readiness. Act as client-facing data scientist, coordinate offshore teams, contribute to MLOps, model monitoring, and deployment on cloud analytics platforms.

As a Data Annotation Specialist, you will label, audit, and optimize data for AI models in Chinese while ensuring high accuracy and quality. You will perform repetitive tasks and collaborate with teams, providing feedback and recommendations for data improvement.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Build and operate a reliable data platform: monitor infrastructure and pipelines, automate platform tasks, manage IaC and CI/CD, support RBAC and governance, contribute to data pipelines and migration, document runbooks, and participate in on-call incident response while improving AI-assisted engineering workflows.

Build statistical and predictive models to measure and optimize marketing, sales, and customer success impact on pipeline, bookings, ARR, retention, and expansion. Analyze paid media performance and conversion funnels, design experiments and causal measurement, forecast revenue, partner with cross-functional teams to define metrics, and communicate data-driven recommendations to senior leadership while improving measurement methodologies and data quality.

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The Data Platform Marketing Manager will lead marketing strategies for DoiT's data lake and Snowflake optimization business, aiming to drive growth and impact.

Lead data analysis, migration planning, and data quality for a province-wide CIS migration. Develop ETL specs, perform data profiling, manage stakeholder collaboration, and ensure accurate, compliant migration of legacy hospital data into the new Clinical Information System.

Lead design, development, and deployment of GenAI and NLP solutions (RAG, LLM-powered apps, agentic AI, Document Intelligence). Work with clients to translate business needs, build end-to-end ML pipelines, mentor teams, present results to stakeholders, and operationalize scalable, governed AI systems.

Design and own end-to-end Azure-based data platform architecture using Databricks. Define ingestion, transformation, governance (Unity Catalog), and delivery standards; optimize performance and cost; integrate with Azure ecosystem and Power BI; mentor teams and guide delivery and CI/CD practices.

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.