Top Data Jobs in Toronto

Support the design, implementation, and maintenance of data workflows and automation for multi-channel marketing, focusing on reliable data solutions and campaign activation.

Lead the delivery of scalable kdb+ solutions for financial clients. Design robust architectures, mentor developers, and drive innovation in data management.

Develop and maintain kdb+ applications, analyze time-series data, mentor junior developers, and collaborate with teams to deliver solutions.

Lead and develop Tableau-based reporting for market risk, manage a team of developers, and ensure optimal performance of business intelligence solutions.

The Senior Manager will oversee data governance, analytics, and insights for the Finance organization, enhancing data quality and operational efficiency.

The Senior Marketing Data Analyst will develop reporting frameworks, analyze data to support Product Led Growth, and create dashboards for stakeholders.

The role involves analyzing large datasets using advanced algorithms, developing predictive models, collaborating with teams, and providing insights for business decisions.

As a Senior Data Platform Developer, you'll build and maintain Geotab's machine learning and generative AI platforms, ensure system health, and support data processing initiatives.

The Senior Data Scientist will collaborate on AI projects, develop scalable code, ensure software quality, and guide product research and development.

The Product Analyst will analyze data to uncover trends, track metrics, build dashboards, and collaborate with various teams to drive data-informed decisions.

As a Data Engineer at Zapier, you'll build scalable data systems, enhance product functionality through data, and collaborate with teams to improve data access and usability.

Design and develop eBay's Core Data Platform, focusing on building scalable distributed systems for data ingestion, governance, and analytics. Collaborate across teams to ensure reliability and enhance data processing capabilities.

As a Senior Data Scientist, you will design AI solutions, lead NLP implementation, and mentor junior staff while transforming data into actionable insights.

The Data & AI Consultant at Kyndryl drives solution development in Data & AI, gathers requirements, and provides architecture for data solutions, focusing on client success and relationship management.

The Associate Director of Data & AI will lead transformation programs, drive business value through AI strategies, and oversee modern data platform delivery for major enterprises.

The Data and Analytics Lead will enhance proprietary datasets, develop analytical models, manage data, and collaborate on business analysis within the Private Market Valuations team.

Lead the Product function for data developer experience teams, improve tools, track metrics, and collaborate with cross-functional teams to innovate in data application.

The Manager, Data Science will lead a team to develop AI and machine learning models, support product features, and drive data applications across the organization.

The Data Engineer will design and develop a Dynamic Data Engineering framework, enhance data lake platforms, and ensure accuracy of data for analysis and reporting.

The Senior Data Scientist will design and maintain metrics, reports, and dashboards, develop algorithms, conduct data analysis, and collaborate with teams to enhance business decisions.

The Data Scientist will use advanced analytics and AI to drive value creation in a portfolio company, focusing on customer insights, operational optimization, and targeting strategies.

As VP, Head of Analytics, Data Science & Pricing, you will lead data-driven strategies to drive growth and inform business decisions, promoting Human+AI collaboration.

This role involves bridging business and technical teams, managing BI tools, optimizing data workflows, and ensuring reliable reporting practices.

The role involves designing, developing, and maintaining scalable low latency streaming solutions using technologies like Apache Flink and Kafka, while leading projects and enhancing team practices.

The Director of Fraud and Risk Management will lead the COE, develop strategies for fraud prevention, and improve compliance, collaborating extensively across teams.