Top Data Jobs in Toronto

Develop and implement advanced machine learning models for pricing strategies and recommendations, collaborating with teams to enhance consumer value and optimize user experiences.

The Senior Data Scientist will lead data analysis projects, develop machine learning models, and translate business needs into actionable insights.

The Data Analyst collects and analyzes data to enhance logistics, creating dashboards and standardizing reports to support performance improvements.

Lead data stewardship initiatives within the Sales domain, ensuring effective data governance and driving user adoption for AI and analytics in collaboration with internal teams.

The Data Steward leads the stewardship of data in Finance & Strategy, collaborating with stakeholders to optimize data governance, analytics, and continuous improvement initiatives while ensuring quality and adherence to standards.

As a Data Scientist, you'll develop machine learning technologies, analyze large datasets, collaborate with cross-functional teams, and contribute to enhancing the engineering culture.

The Senior Data Engineer will design and develop Colliers' Global Data Ecosystem, collaborating on data solutions, integrations, and APIs with various teams.

As a Manager of Data Platforms, enhance data-driven strategies by implementing martech solutions, collaborating with clients, and ensuring compliance with data operations.

As a Data Engineer, manage data migration by evaluating sources, building ETL pipelines, ensuring data quality, and collaborating with stakeholders.

As a Business Development Intern, you will assist in sourcing acquisitions, conducting market research, and data management in Salesforce.

The Data Analyst will support Go-To-Market teams by providing insights and reporting, developing dashboards, and analyzing data to drive strategic decisions.

The Customer Data Analyst will analyze customer engagement data, support stakeholders with insights, and ensure data accuracy to improve healthcare outcomes.

Lead the design and development of data architecture, focusing on data modeling, integration, and analytics for Scribd's data strategy.

The Customer Success Systems and Data Analyst will manage Gainsight, perform data analysis, track KPIs, and coordinate customer success projects to enhance satisfaction and retention.

The Data Analyst will deliver insights for Product and Marketing, create reports, optimize dashboards, and work on data models and pipelines.

The Data Engineer I will maintain data models, ensure data consistency, collaborate with teams for KPI reporting, and improve data stack efficiency.

The Senior Manager of Data Infrastructure oversees data architecture and infrastructure for analytics, manages data pipelines, ensures data integrity, and enforces data policies. They lead a modern analytics tech stack and integrate various systems, guiding the analytics team toward effective data-driven strategies.