Top Data Jobs in Toronto

The Senior Data Scientist will drive high-impact ML initiatives, translate strategy into models, and connect model performance to business outcomes. The role requires collaboration with stakeholders to improve product ranking, approval likelihood, and member engagement through data-driven recommendations.

Design, implement, and own data-intensive scalable platform components, while mentoring engineers and debugging production issues in a fast-paced environment.

The Data Engineer will develop and optimize ingestion pipelines, ensure data accuracy, and support automation initiatives for high-volume data workflows.

The program develops analytical expertise through two 12-month rotations, focusing on data science, business intelligence, and insights for business growth at Canadian Tire Corporation.

The Director of Data Science will lead the data science team, develop predictive models, and enhance AI strategies to drive business growth.

The Data Analyst will analyze energy market data to forecast peak demand, improve forecasting models, and collaborate with cross-functional teams to optimize battery energy storage operations.

As a Data Engineer at ODAIA, you'll design and implement scalable data solutions, manage customer data integration, and support analytics capabilities while collaborating with cross-functional teams.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

The Data Engineer will manage the full data stack, design database architecture, build ETL pipelines, create data integrations, and oversee reporting and data quality.

The Software Engineer will provide technical support to customers, collaborate with engineering teams, and drive customer success initiatives while leveraging Python and SQL expertise.

Develop and enhance data source integrations, improve systems based on metrics and feedback, drive architectural discussions, and participate in on-call rotations to ensure reliability.

Lead the development of API portal and data integration frameworks, managing a team of data engineers to ensure data accessibility and security.

Design and build scalable distributed ingestion services; maintain event pipelines and collaborate with multiple teams. Ensure system reliability and improve code practices.

The Head of PT Data Acceleration leads Roche's data strategy, manages a team, and drives a data-first culture in Pharma Technical Operations.

The Data Scientist will analyze customer health, conduct quantitative research, develop insights for teams, and inform strategy based on data analysis.

The Data Analyst will analyze datasets, create visualizations, generate reports, and collaborate with teams to provide actionable insights using Power BI and SQL.

The Data Engineer is responsible for designing and optimizing data pipelines, ensuring data integration, and collaborating with teams on AI-driven applications.

Design and implement scalable data architectures, establish data governance, oversee ETL processes and collaborate with teams to enhance data infrastructure.

The Data Engineer will design and maintain ETL pipelines, work with Snowflake for data warehousing, ensure data quality, and collaborate on analytics initiatives.

The Senior Cloud Systems Engineer will design, implement, and manage cloud infrastructure, ensuring security, compliance, and high availability while leading team initiatives and collaboration across functions.

Design, implement, and manage Azure cloud solutions with a focus on automation. Develop CI/CD pipelines, ensure security compliance, and mentor IT team members.

The Senior Data Engineer will design and maintain data pipelines, support data migration projects, and mentor team members in a transforming data environment.

As a Senior Data Scientist, you will develop machine learning models for logistics, credit assessment, retailer growth, and optimize marketing efforts to enhance customer acquisition and engagement.

Lead a team of data analysts to improve product performance insights, establish experimentation practices, and enable self-service insights for the company.

The Data Scientist will solve real-world problems utilizing data science techniques and build end-to-end data pipelines, collaborating with multiple teams to deliver solutions.