Top Data Jobs in Ottawa

Build and operate ML training and serving infrastructure: design, develop, and launch backend systems, support availability and on-call, collaborate cross-functionally, and improve developer velocity.

Build and productionize statistical and ML models for Toast's restaurant platform. Partner with engineers, product, and business teams to mine data, design experiments, evaluate models, and communicate actionable insights that drive product growth and customer outcomes.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, run causal and bandit experiments, decompose merchant economics, and develop agentic deal tooling. Own end-to-end data pipelines, ETL, monitoring, and visualization. Evaluate AI systems for accuracy, bias, and drift, and partner with cross-functional teams to translate results into pricing strategy and automation.

Lead design and operation of Block's real-time, event-driven data systems. Build and run high-throughput streaming pipelines, turn Kafka event streams into low-latency data products, improve reliability and observability, mentor engineers, and define platform architecture and standards for projections, third-party data proxy, and graph data capabilities.

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.

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

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.

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.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Leads architecture and development of large-scale batch and real-time data platforms and pipelines. Ensures data quality, governance, reliability, observability, scalability, and cost efficiency while building self-service capabilities. Supports analytics, machine learning, and generative AI teams with trusted data infrastructure. Establishes engineering standards, mentors engineers, and drives platform health across multiple teams. The role requires expertise in data integration, distributed processing, data modeling, cloud platforms, CI/CD, and infrastructure automation.

Build and operate production-grade data ingestion and transformation pipelines in Databricks using Spark/PySpark, SQL, Delta Lake, and medallion architecture. Manage schemas, data quality, deduplication, API integrations, orchestration, monitoring, alerting, recovery, and performance optimization. Collaborate with data scientists and application teams to provide reliable data for LLM/NLP pipelines. Contribute to CI/CD, documentation, data architecture, and onboarding new data sources.

Perform Sage Intacct data migrations, ETL, validation, reconciliation, cleanup, integrations, customizations, workflows, and automations. Support ERP implementation projects, troubleshoot data and web-service issues, create reports and templates, and train customers on data management tools and best practices. Collaborate with clients and internal teams to solve data challenges, estimate project requirements, and integrate Sage Intacct with CRM, construction management, payroll, and other systems. The role is remote with travel up to 20%.