Top Data Jobs in Ottawa

Leads strategic pricing and monetization across sales-driven channels, managing pricing partners and advising on complex commercial deals. Develops pricing frameworks, approval processes, deal governance, and scalable tools using automation, AI, and data. Partners with Sales, Product, Engineering, Legal, Risk, and Revenue Operations to improve deal economics, profitability, pricing performance, packaging, and portfolio-level monetization strategy.

Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Sets the technical vision for data science, leads complex credit risk, pricing, and loss forecasting models from conception through production, and architects scalable machine learning pipelines. Partners with senior stakeholders to shape strategy, establishes modeling and validation standards, mentors technical staff, and communicates recommendations to executives. The role requires deep fintech lending experience, advanced statistical and machine learning expertise, and hands-on production model deployment.

Develop customer-specific AI solutions for consequential business decisions. Investigate internal and public information, evaluate evidence, identify uncertainty, and design reliable AI workflows. Work directly with customers to understand needs, prototype solutions, test them with users, and improve their usefulness. Translate successful workflows into repeatable product capabilities while partnering with engineers on integrations and missing technical functionality.

Design and build scalable backend systems, APIs, data models, event-driven services, experimentation platforms, and personalization systems. Partner with Product, Data Science, Analytics, and Design teams to support customer acquisition and engagement. Establish secure, observable, high-performance engineering practices, mentor junior engineers, and participate in monitoring, on-call, and operational support.

Leads partner-led and enterprise sales growth, primarily through AWS and Microsoft ecosystems. Builds strategic partnerships, develops enterprise accounts, drives end-to-end sales cycles, expands SMB sales processes, positions cloud and digital engineering capabilities, and manages pipeline forecasting. The role also helps shape sales strategy, organization, and scalable go-to-market processes.

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.

Lead data science initiatives for Risk and Support Operations by analyzing customer and product data, defining metrics, forecasting demand, evaluating experiments and risk policies, and building decision frameworks. Use AI tools and agent workflows to improve analytical efficiency. Partner with product, engineering, and risk teams, communicate insights to senior stakeholders, establish technical standards, mentor data scientists, and support hiring.

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, workflow automation, evaluation, and observability capabilities. Work hands-on with Python, SQL, dbt, lakehouse data, cloud infrastructure, model selection, and inference-cost optimization. Establish reusable engineering patterns and mentor teams through high-quality code and system design.

Analyze product, customer, risk, and support data to guide decisions across Block’s platforms. Own metrics, forecasting, staffing models, experiments, visualizations, and measurement frameworks. Evaluate risk models and policies for performance, bias, and drift; use AI tools and agent workflows to improve analytical execution. Partner with product, engineering, and risk stakeholders, lead technical standards, build reusable tooling, mentor data scientists, and contribute to hiring.

Designs and delivers secure, scalable Azure cloud, data, analytics, database, and AI solutions for customers. Leads architecture, roadmaps, proofs of concept, production deployments, workload optimization, governance, resiliency, and security initiatives. Partners with technical and business stakeholders, supports customer adoption and Azure consumption, resolves technical blockers, contributes reusable deployment frameworks, and mentors others. Requires strong expertise in Microsoft Fabric, Azure Databricks, Purview, Azure databases, data engineering, governance, migration, and cloud architecture.

Leads complex data science and analytics initiatives, develops and validates predictive models, evaluates diverse data sources, and translates findings into actionable business insights. Determines technical approaches, supports risk mitigation and decision-making, and provides technical leadership and mentorship to analytics professionals. Collaborates with stakeholders while promoting quality, consistency, and data-driven solutions.

Drive strategic federal sales growth across DISA 4th Estate and Intelligence Community accounts. Responsibilities include pipeline development, account planning, opportunity and win strategy, stakeholder relationship development, acquisition navigation, RFI and solicitation support, CRM management, forecasting, and translating technology solutions into mission outcomes. The role requires expertise in long-cycle federal sales, procurement processes, secure environments, and technology solutions.

Drives adoption of the enterprise data governance framework across business and technology domains. The role deploys governance tools and policies, coordinates data teams and working groups, tracks roadmaps and milestones, supports data quality initiatives, maintains documentation, and develops dashboards and executive briefings. It also facilitates stakeholder education, workshops, communications, and action-item tracking while partnering with engineering and BI teams.

Lead CBC/Radio-Canada’s enterprise data governance program, including policies, data classification, catalogs, metadata, quality, lineage, compliance, and AI readiness. The role oversees governance councils, data stewards, executive reporting, literacy initiatives, and a small governance team. Responsibilities include partnering with Legal, InfoSec, engineering, analytics, and business stakeholders to establish consistent data management practices across a national, matrixed organization.

Drive technical sales and customer adoption of Microsoft Azure cloud database and analytics solutions through demos, proofs of concept, hackathons, and architecture workshops. Advise customers on secure, scalable data-platform architectures, migrations, and AI applications. Build relationships with technical decision-makers, resolve implementation blockers, collaborate with engineering teams, and maintain expertise across Microsoft Fabric, Azure Databases, Databricks, Purview, and competing data platforms.

Collect and prepare data, apply statistical inference and advanced analytics, and visualize insights to support business decisions and strategic planning. Translate business problems into scalable data science solutions, collaborate with analysts, engineers, and developers, and promote statistical validation, risk management, governance, and continuous improvement. The role independently handles complex projects, advises stakeholders, and may mentor others.

Sells new business and manages and expands client portfolios for CoStar’s commercial real estate data and analytics products. Responsibilities include prospecting, product demonstrations, consultative selling, closing, onboarding, training, renewals, account management, client meetings, and industry event representation. The role requires exceeding sales targets, building client relationships, and developing expertise in commercial real estate markets and CoStar products.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

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.

Supports the analysis and definition phase of an Intelligence Mission Data project. Gathers and documents requirements, facilitates workshops, develops use cases and system specifications, performs technical options analysis, evaluates solution compliance, assesses organizational impacts, and supports testing and integration. The role also prepares briefings, meeting records, action reports, and progress updates while collaborating with users, customers, stakeholders, and project personnel.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.