Top Data Jobs in Ottawa

The GTM Lead for Insurance will build and manage enterprise insurance accounts, develop relationships with senior industry leaders, and shape sales strategies for AI solutions.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, forecasting, targeting, and personalization. Collaborate with engineers and product teams, set modeling and productionization standards, mentor data scientists, guide architecture and experimentation, and apply cloud and MLOps best practices to drive measurable product and business impact.

The Senior Data Platform Engineer at 1Password will design, build, and maintain data systems and streaming architectures, ensuring data quality and governance for real-time access.

Build scalable GCP-based data pipelines and datasets for insurance fraud analytics. Develop and evaluate machine learning, NLP, and Generative AI models using claims and unstructured SIU data. Apply explainable AI techniques, conduct exploratory analysis, automate data workflows, document architectures, and support privacy, fairness, and compliance requirements while collaborating with investigators and business analysts.

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.

The Software Engineer will manage data collection for model training operations, enhance cloud infrastructure, and collaborate with AI scientists to improve data quality and scale.

Support client engagements measuring de-identification and re-identification risk for datasets (especially healthcare). Validate and prepare data, perform qualitative and quantitative risk analyses, document results in client-facing reports, prepare presentations/materials, assist deliveries and remote coaching, and develop expertise in privacy regulations and statistical disclosure control.

Lead advanced analytics projects to build, validate and monitor predictive and descriptive models. Determine technical approaches, evaluate diverse data sources, translate findings for stakeholders, and provide technical leadership and mentorship to analytics teams to support business decisions and risk mitigation.

Manage and coordinate security projects and operations for the Corporate Security Office, supporting project lifecycle from planning to close-out. Provide data analysis, site inspections, hardware/software testing, security screenings, and policy/maintenance plan development while coordinating stakeholders and technical teams.

Provide on-site configuration and data management support for NASA AFRC projects: maintain CM plans and repositories, control configuration items and engineering changes, administer CCBs and ACMS/ACCT, run audits (PCAs), track action items and metrics, and train users on CM tools and processes.

CommBank is seeking Indigenous job seekers for various roles across its sectors, offering traineeships, internships, and direct employment opportunities with support from an Indigenous Careers team.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Lead a hybrid engineering and data platform team to build scalable software and data infrastructure. Oversee Power Platform deployments, data architecture, governance and compliance (GDPR/HIPAA), BI/analytics, DevOps automation, and integration of AI/LLM and agentic solutions to drive intelligent automation and platform scalability.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

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.

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

Drive technical pre-sales for Microsoft cloud database and analytics solutions via demos, PoCs, hackathons, and architecture workshops. Design secure, scalable data architectures, resolve technical blockers, collaborate with engineering, and evangelize Microsoft Fabric, Azure Databases, Databricks, Purview and EDW migrations to accelerate customer adoption.

Lead design, development, and optimization of enterprise data solutions. Build and maintain data pipelines, warehouses, and analytics platforms. Apply data governance, quality, metadata, and lineage practices. Ensure data security and compliance, monitor platform performance, and collaborate with stakeholders while providing technical guidance and mentorship.

Lead operational management and support of the enterprise data platform (primarily Snowflake), ensuring stability, scalability, observability, incident management, and migration from SQL Server. Manage data operations team, establish runbooks/SLAs, coordinate cross-functional readiness, drive continuous improvement, and ensure governance, compliance, and performance of data pipelines and platform services.

Take end-to-end ownership of backend features and SaaS services in a microservices architecture. Design, implement, deploy, and operate scalable, reliable Node.js services. Work with Redis Streams, MongoDB, Kubernetes, and ensure test coverage, performance tuning, and collaboration with cross-functional teams.

Lead global data and AI engineering to deliver scalable, secure, and compliant data platforms and MLOps capabilities. Own strategy, architecture, operations, SRE practices, observability, and reusable self-service components to support analytics, AI, and enterprise programs.

Design and analyze experiments and causal studies, build retention measurement and predictive models, develop scalable PySpark/SQL data pipelines, create dashboards, and partner with product and growth teams to improve user engagement and retention.

Lead technical strategy and hands-on implementation for Faire's data platform. Architect and scale ETL/ELT, streaming and batch pipelines, data warehousing, orchestration, monitoring, cost optimization, security, and governance. Mentor teams, prioritize platform roadmaps, and partner with product, analytics, and data science to enable self-serve data capabilities across the company.