Top Data Jobs in Ottawa

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.

In this role, you will define and execute the go-to-market strategy, drive growth, and lead customer success efforts at Reflow, a workplace intelligence platform.

As a Product Manager at Reflow, you will lead product strategy, execution, and delivery while ensuring customer engagement and managing engineering dependencies in an early-stage startup environment.

The Director of Product Management will lead product strategy across infrastructure, software enablement, and customer-facing platforms, enhancing both technical and user experience while managing a team of product managers.

Lead executive interviews, stakeholder workshops, and current-state assessments to identify operational gaps and opportunities. Develop business cases, operating models, governance, KPIs, roadmaps, and practical AI-enabled solutions. Advise on AI strategy, innovation, commercialization, customer experience, and change management. Support transition of recommendations to delivery teams and occasionally participate in business development.

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.

Lead options analysis and systems definition for an Intelligence Mission Data project: gather and trace business requirements, develop system use cases and specifications, evaluate technical solutions, plan organizational impacts, support integration and testing, and prepare briefings and project documentation.

Design and implement data platform architecture, ETL/ELT pipelines, data mappings/lineage and quality rules. Build orchestration workflows, support data migration and CBM initiatives, deploy and monitor AI/ML models, and collaborate with analysts and stakeholders to deliver production-ready data solutions.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Lead marketing analytics and data strategy for B2B SaaS Marketing. Design measurement frameworks, own attribution, funnel and lifecycle analysis, forecasting, and marketing investment recommendations. Partner with senior marketing leaders and cross-functional teams to build data foundations, enable AI-assisted analytics, and mentor analysts to raise analytical standards.

Senior Data Analyst partnering with Marketing to measure attribution, funnel performance, forecasting, and lifecycle metrics. Build analytical frameworks, scale AI-assisted analytics, work with cloud data stacks, BI tools, and martech to inform marketing decisions and improve data foundations.

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.

Design, build, deploy, and support BI, reporting, dashboards, semantic layers and analytics solutions. Translate business requirements into scalable BI deliverables, write and optimize complex SQL/BigQuery queries, ensure data quality and governance, follow SDLC and DevOps procedures, monitor and tune BI environments, and collaborate with cross-functional teams to deliver reliable analytics.

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 analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

Manage technical data for IP Routing hardware NPI programs: support NPI from data entry through factory implementation, maintain product data and Engineering Change Orders across the product lifecycle, and coordinate with engineering, supply chain, and manufacturing to ensure accurate PLM/PDM records and implementation.

Design, build, and maintain robust terabyte-scale data pipelines and stream-processing applications. Collaborate with product teams, participate in full SDLC, automate tests and deployments, monitor operations, and contribute to technical strategy and continuous improvement. Participate in on-call rotation.

Lead multidisciplinary design projects for mission-critical data centres across North America. Manage schedules, budgets, resources, coordination among electrical, mechanical, structural, and BIM teams, ensure code compliance, mitigate risks, support contracts and business development, mentor staff, and travel occasionally for client meetings and site visits.

Design and execute data quality strategies for enterprise data platforms. Test ETL/data pipelines, perform source-to-target reconciliations, build validation frameworks, write complex SQL for analysis, perform regression testing, root-cause defects, and collaborate with engineers and stakeholders to improve data integrity.

Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.

Design and optimize data pipelines, lead machine learning feature integration, mentor junior engineers, and enforce data governance.

Design and build operational data systems, including pipelines, storage layers, and APIs for near real-time enforcement and insights, balancing streaming and batch paradigms.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.