Top Data Jobs in Ottawa

The Enterprise Solutions Manager drives operational excellence and client success through strategic analysis, process optimization, and project management, collaborating with various teams to deliver AI solutions.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

The role involves designing and implementing scalable data models using Data Vault techniques on Azure. Responsibilities include collaborating with stakeholders, optimizing data vault models, ensuring data security, and documenting data processes.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from ad platforms, order systems, and real-time events. Ensure reliability, observability, and maintainability across event-driven and batch architectures, implement authentication flows, optimize data workflows in a cloud-native environment, and collaborate with product, infrastructure, and data teams to onboard new sources.

Data Contributors will research startups, analyze global data for StartupBlink's Global Startup Ecosystem Index, and compile accurate information for publication.

Lead enterprise-wide AI adoption by translating technical AI concepts for non-technical stakeholders, curating education and communications, partnering with change management and L&D, triaging requests, and building a team to drive measurable AI adoption across the organization.

Senior Data Scientist for Rovio's Beacon platform in Espoo. Develop predictive and statistical models for User Acquisition, handle long-term forecasting, uncertainty quantification, optimization, and rare-event behavior. Translate research into production, own model lifecycle from experimentation to deployment and monitoring, and collaborate closely with UA, game teams, finance, analysts, and engineers while contributing to a collaborative modelling culture.

Design and optimize SQL Server solutions, manage data, automate processes with PowerShell, and integrate with external systems to enhance functionality.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

As a Backend Engineer on the Data team, you will design and maintain data pipelines and services, ensuring data quality and scalability while collaborating with cross-functional teams to meet data needs.

Lead strategic architecture for front-office investment technology and data solutions, advising on platform selection and implementation (Aladdin, Charles River, Bloomberg, etc.), guiding data architecture, governance and quality, managing small-to-medium implementation teams, and ensuring delivery across portfolio management, trading, and reporting domains.

Lead a distributed team of data scientists and engineers, focusing on data infrastructure and ML systems while collaborating with product and marketing teams.

Use customer, digital, and transportation data to build targeting, propensity, pricing, loyalty, and churn models; run experiments (A/B), optimize promotions and pricing, present insights to stakeholders, manage data structures in Databricks/AWS, and lead project work with business partners to drive data-driven decisions.

Manage relationships with strategic healthcare clients, oversee complex projects, innovate operational processes, and lead large teams to improve AI training and application.

Own analysis and algorithmic solutions for ads delivery; train, deploy, and scale ML/optimization models into production; build logging, monitoring, and lineage; improve data pipelines; mentor data scientists; use agentic AI tools daily; collaborate with engineers to integrate models into ads systems and handle on-call production incidents.

Analyze player behavior, game health, engagement, retention, monetization, and live-service performance for Marvel Strike Force. Own KPI reporting, explain trends and variances, evaluate experiments, validate analytics tracking, and deliver actionable insights to product, design, marketing, live operations, and leadership teams. Use SQL, Python, reporting tools, and AI-enabled workflows while maintaining data quality, privacy, and analytical rigor.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Own the end-to-end data science function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence leadership decisions. The role requires independently structuring ambiguous problems, using SQL or Python, communicating findings clearly, and driving measurable business outcomes.

Own the end-to-end analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to influence decisions and drive measurable outcomes. The role requires strong analytical ability, independent problem-solving, clear communication, and ownership of ambiguous initiatives.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, and deliver actionable insights. Partner with product, growth, finance, and operations leaders to communicate findings, influence decisions, and drive measurable outcomes. The role requires strong analytical problem-solving, independent execution, and persuasive communication.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, pull and structure data, build reports, run analyses, design experiments, communicate insights, and drive recommendations and decisions with cross-functional stakeholders. Requires strong analytical thinking, independent execution, persuasive communication, and experience solving ambiguous problems in consulting, investment banking, or high-growth technology.

Own end-to-end data science for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires independent analytical execution, first-principles problem solving, persuasive communication, and ownership of ambiguous initiatives that drive measurable business outcomes.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate insights; and drive decisions and measurable outcomes with cross-functional stakeholders. The role requires independent data work, strong problem-solving, persuasive communication, and ownership of ambiguous initiatives from end to end.

Own and evolve high-throughput backend services that deliver machine learning-powered predictions to merchants. Responsibilities include API design, service decomposition, Python development, PostgreSQL and Kafka integration, distributed systems reliability, observability, feature pipelines, ML serving, model deployment, versioning, rollback, and prediction monitoring. The engineer will partner with Data Science, lead architectural decisions and technical reviews, mentor teammates, and establish strong engineering practices for production data products.

As a Data Analyst at Stripe, you'll build data products, metrics, and dashboards, analyze large datasets, and communicate insights to drive business decisions.