Top Data Jobs in Toronto

Internship involves analyzing data, building machine learning models, collaborating with Data Scientists, and presenting insights to drive business strategy.

Data Scientists at Stripe analyze data, build models, run experiments, and collaborate with teams to optimize business decisions and strategies.

This role involves outbound prospecting, conducting cold calls, emails, and LinkedIn outreach to qualify opportunities and set meetings in a remote capacity.

The AVP, Cyber & Data Risk at Aviva Canada will lead oversight of data privacy, governance, and cybersecurity, driving effective risk management and compliance initiatives across the organization.

Design and maintain data pipeline architecture, manage AWS services, optimize data systems, and ensure efficient ETL operations across various data sources.

Lead delivery of data and analytics initiatives, manage Oracle ERP projects, and implement AI for SDLC improvements while ensuring strong governance and stakeholder management.

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

As a Data Engineer, you'll develop and manage data ingestion pipelines, model data for analytics, and ensure data quality across advertising platforms.

As a Data Analyst in People Analytics at Lyft, you'll manage data requests, build ThoughtSpot dashboards, and enhance insights using AI capabilities. You'll collaborate with HR to craft metrics and translate findings into actionable insights for leadership.

Lead the strategy and execution of Beacon's data platform, integrating technology stacks and developing AI-powered workflows to support BD and M&A functions.

The Data Engineer II will perform data engineering functions such as data modeling, ETL, and data quality management while collaborating with various teams and maintaining compliance with data standards.

The IT Data Specialist provides technical leadership in data analysis including data modeling, ETL, reporting design, and ensures data quality management, collaborating with business and technology partners.

Lead end-to-end analytics for business decisions using data insights and AI/ML. Collaborate with cross-functional teams to build scalable solutions and drive advanced analytics adoption, delivering actionable insights and compelling visualizations.

The Data Engineer will provide technical support and deployment expertise, review data designs, and ensure code quality while collaborating with international teams on a strategic data initiative.

Lead and mentor a data science team to enhance the Rider App experience through machine learning, analytics, and experimentation. Partner with stakeholders to drive data-driven decisions and innovation.

Develop and extend data ingestion pipelines for AI model training, manage cloud infrastructure, and collaborate with AI scientists. Bring new audio data sources into the system.

Review and analyze news content from patient advocacy groups, extract insights, and input data into Zebricks to support AI/ML processes. Collaborate with the team on data projects, shape data best practices, and perform web research and spreadsheet-based data work.

Lead enterprise data, analytics, and AI transformation engagements as a strategic advisor and architect. Design cloud data platforms, warehouses/lakehouses, governance, BI/semantic models, and integration strategies. Provide delivery oversight, mentor teams, conduct architecture reviews, and support pre-sales and thought leadership to drive measurable business outcomes.

Perform accurate, timely data entry and document typing/proofreading, organize and categorize records, collaborate with remote team members, and follow company data management policies.

Perform remote data entry tasks: enter, update, verify, and correct information in company databases while maintaining accuracy, confidentiality, and meeting deadlines. Follow instructions and work independently.

Responsible for designing and operating data architecture, building ETL/ELT pipelines, implementing data quality frameworks, and collaborating on ML initiatives.

The Senior Analyst, Growth Analytics (CRM) will own CRM analytics strategy, build measurement frameworks, analyze experiments, track performance, and present insights to leadership to optimize customer retention and lifetime value.

The Big Data Engineer will design and maintain data pipelines, manage AWS infrastructure, optimize ETL processes, and support operational activities while mentoring junior staff.

The Senior QA Analyst will build automation frameworks using Python, validate data pipelines in AWS, and conduct deep-dive SQL analyses to ensure data integrity and system performance in a trading environment.

Design, build, and own streaming data pipelines and feature stores to enable low-latency inference and real-time model serving. Partner with ML and infra teams to define data contracts, ensure data quality, observability, and SLAs, and move batch pipelines toward real-time production. Evaluate streaming and feature store technologies and contribute to inference pipeline tooling.