Top Data Jobs in Ottawa

This role involves deploying solutions for clients, managing data compliance, and providing feedback for product improvement. Requires collaboration with teams and clients.

Lead RWD analysis strategy and execution: develop technical specifications and statistical programs, perform complex observational analyses (propensity scoring, ML), validate cohorts/variables, ensure QC, collaborate cross-functionally, and communicate results to non-technical stakeholders.

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.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The Data Engineer will assist clients with SAP security design, implement SAP security, develop authorization profiles, and conduct security reviews.

Perform quantitative and qualitative data analysis and reporting to support public health research and program evaluation. Produce reports, integrate mixed-methods data, assess implementation measures, advise stakeholders, manage gov/admin systems, and present findings to decision-makers.

Own technical execution of customer data migrations: explore source systems, export data, author declarative version-controlled mappings, transform and validate data, run end-to-end migrations on internal platform, build reusable templates/validation, troubleshoot discrepancies, and document mapping and transformation logic for auditable production cutovers.

Lead the Data Platform product for AISim, owning ingestion, schema reconciliation, lineage/provenance, sensitivity and field-of-use governance, federated data sharing, experiment-integration APIs, and dataset usability metrics. Partner with engineering, science, design, and compliance to turn ambiguous data problems into measurable, scalable platform features.

Lead roadmap and deliverables for measurement products (attribution, ABM, first-party data), create 0→1 solutions, write clear product specs, and drive features to completion working with engineers, designers, QA, and cross-functional teams.

Join the centralized Analytics team to measure product features, build and maintain dashboards, analyze clickstream and behavioral data, support A/B testing and feature measurement, and communicate insights to Product, Engineering, and Design. Grow technical skills with mentorship and contribute to Generative BI and AI-assisted analytics workflows.

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.