Top Data Jobs in Toronto

The Data Scientist will collaborate with teams to solve business problems through data analysis, clean and preprocess data, apply statistical methods and machine learning models, communicate insights through data visualizations, and continuously improve analytical processes.

As a Data Analyst at Stripe, you will extract insights from complex datasets, build data products, and deliver actionable recommendations. Collaborating across teams, you will translate business needs into data problems, developing scalable data pipelines and dashboards to inform decision-making.

As a Data Engineer at Provectus, you will build and maintain data pipelines, collaborate with Data Scientists, and create data models. Your role includes working with cloud platforms and various data tools to manage large data sets and support Generative AI applications and internal projects.

As the Manager of Data Analytics, you will lead a team of analysts and scientists to drive Dialogue’s data strategy and build data products that support decision-making across the organization. You will manage stakeholder relationships, drive the data products roadmap, and collaborate closely with the Data Engineering team to ensure robust data operations.

The Senior Manager - Data Engineering/Reporting will lead data engineering and reporting projects, translating business problems into engineering solutions, managing teams, and presenting analytic solutions to stakeholders. Responsibilities include hands-on work with SQL and data visualization, while ensuring best practices and collaboration with internal teams and clients.

Looking for a Data Engineer with 4+ years of experience in IT industry, expertise in Python and Pyspark, and experience building data pipelines using Azure stack. The candidate should have strong analytical skills and the ability to align data systems with business goals.

The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges.

The Staff Data Scientist will work with large text data, performing data extraction, cleaning, processing, and analysis. Responsibilities include running experiments on AWS Sagemaker, deploying models, and collaborating with data engineers and stakeholders on high-impact projects in Generative AI and Natural Language Processing.