Top Data Jobs in Toronto

As a Software Engineer on Glean's Data Foundations team, you'll build and scale data ingestion connectors, transforming unstructured content into structured data while ensuring system reliability and security throughout the data processing pipeline.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

Join VAST Data as a Senior Software Engineer to design and implement backend components for a scalable, AI-native vector database, focusing on low-level systems programming and distributed computing.

The Director of Data Strategy will develop and execute a data strategy, ensuring data quality and governance across the organization, fostering collaboration among various departments for improved analytics and business outcomes.

The Principal Data Architect will design and evolve enterprise data architecture to support business growth and AI integration, ensuring a secure and efficient data ecosystem while collaborating with various teams to enhance data quality and governance.

Develop, validate, and deploy supervised and unsupervised machine learning models; transform and analyze large structured and unstructured datasets using Python, SQL and BI tools; apply OCR and NLP techniques; maintain source control and MLOps processes; present findings via dashboards and reports to technical and nontechnical stakeholders.

The Manager of Financial Data, Planning & Analytics oversees financial planning and analysis, modernizes financial systems, and drives automation in reporting and forecasting, while acting as a strategic partner to leadership.

This role involves managing the People tech stack, building analytics and dashboards, improving HR systems, driving innovation, and ensuring operational excellence across people processes.

The role involves building scalable data platforms, designing ETL pipelines, collaborating with cross-functional teams, ensuring data quality, and mentoring others in data engineering best practices.

The Staff Product Data Analyst will drive analytics for game titles by developing dashboards, predictive models, and automating workflows, impacting player engagement and monetization strategies.

The Data Scientist will work with fraud product owners to deploy fraud solutions, analyze complex data sets, and enhance predictive analytics while mentoring others.

The role involves researching and applying advanced modeling techniques in advertising technology, experimenting to validate results, and mentoring junior team members.

Lead the engineering vision and execution for the Customer & Business Insights Platform, focusing on data architecture, pipelines, and product delivery while mentoring global teams and ensuring data governance.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

The AI Data Engineer will build scalable data pipelines, design systems for data processing, and manage the lifecycle of AI agents, focusing on unstructured data such as video and audio.

As a Founding Senior Data Engineer, you will build the analytics foundation, design data pipelines, track metrics, and collaborate with teams for data-driven decisions.

Build and maintain a unified marketing performance dataset, design and QA data pipelines, create self-serve dashboards and forecasting tools, analyze acquisition efficiency and CAC/LTV, support marketing and finance with reconciliations, and provide data-driven insights for growth strategy and spend optimization.

Maintain and improve data processes for a MedTech market-intelligence product: review and extract insights from news, hunt new company/data sources, ensure high-quality recurring processes, use LLMs to extract key company/device information, and deliver on timelines for data tasks and projects.

Lead ML research in security: design and run experiments, curate and label data, develop features and models, publish findings, integrate models into production, and support model lifecycle and internal tooling.

As a Data Engineer at LiveKit, you will manage the analytics infrastructure, develop scalable GCP-based data pipelines, and ensure effective data movement and transformation processes, while collaborating with the Analytics and engineering teams.

In this role, you will develop data pipelines, dashboards, and conduct A/B tests while providing insights for strategic decisions across teams.

The Data Scientist will support model development for personalization and customer engagement, analyze data, and integrate models into production workflows.

As a Data Engineer, you will design and implement scalable data pipelines and solutions, collaborate with teams, and apply new technologies in an Agile environment.

The Data Engineer will design scalable data pipelines, manage data solutions, collaborate with teams, and ensure project delivery on time while applying new technologies.

The Director of Data will lead the evolution of ZayZoon's data platform, managing a team while enhancing data governance and analytics to support business growth.