Top Data Analytics Jobs in Toronto

The Staff Analytics Engineer will lead cross-team projects, develop scalable data models, optimize SQL queries, and champion centralized data assets to support product launches and data initiatives. The role requires collaboration with various stakeholders and a strong focus on data-driven decision-making.

The Senior Data Scientist will analyze product metrics, develop queries, and create dashboards to support data-driven decisions within Geotab. Responsibilities include interpreting large datasets, writing SQL queries, identifying data quality issues, and collaborating with product teams to understand analytics needs.

As an Analytics Developer, you'll support the Fraud and Anti-Money Laundering teams by transforming data, building metrics, and collaborating with stakeholders to address their data needs. You'll also implement data controls for accuracy and help mitigate fraud losses while contributing to analytics best practices.

The Senior Data Scientist will leverage expertise in Data Science and AI to design and build advanced analytics engines. Responsibilities include developing analytical models, collaborating with cross-functional teams, and ensuring business value through effective communication of results.

The HR Systems & Analytics, Workday Lead is responsible for the strategy, implementation, support, and maintenance of HR systems, specifically Workday. Duties include analyzing HRIS performance, managing system maintenance, conducting audits, enhancing system configurations, creating custom reports, and providing training for end users.

As a Sales Representative for CoStar Data & Analytics, you will engage potential clients, manage and grow the existing client base, and promote CoStar and LoopNet products. You will handle the full sales cycle, conduct product demonstrations, and network within the commercial real estate industry, all while helping clients understand their needs and providing tailored solutions.

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.