Top Data Jobs in Toronto

The Staff Data Scientist will lead data science projects, develop machine learning models, and align solutions with business goals while mentoring team members.

The Lead Data Scientist will design and implement data-driven solutions, lead a team of data scientists, and collaborate across functions, while managing machine learning pipelines and mentoring junior staff.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

As a Staff Backend Engineer, you will develop complex backend solutions, focusing on the Spark-based data platform while ensuring code quality and collaborating closely with teams.

Lead subscription analytics: define KPIs, design experiments (A/B tests), analyze customer lifecycle, identify retention/growth opportunities, ensure data quality, and build dashboards to inform cross-functional decisions.

Perform high-level video captioning, action-based timeline segmentation, and visually-verifiable action labeling. Review and correct AI-generated captions, meet accuracy benchmarks, follow strict guidelines, and complete certification.

The Product Owner will define and prioritize backlog items for Autodesk's AEC Platform Data team, focusing on information requirements management and collaborating with clients and cross-functional teams.

As an Android Engineer, you'll enhance automated tools for analyzing APKs, improve dynamic analyzers, and collaborate on security checks for Android applications.

Design, build, and optimize cloud-native lakehouse data pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, observability, governance, and reusable platform patterns to support analytics, embedded reporting, operational workflows, and AI/ML datasets. Mentor engineers, lead reviews, and improve platform reliability, cost efficiency, and data quality.

Own and build Snowflake-based data platform and ELT pipelines from SaaS sources into Snowflake, using Snowpark Python workloads. Design schemas, enforce governance, implement data quality and monitoring, optimize performance and cost, and enable AI-ready datasets (embeddings, feature stores, Cortex functions). Partner with RevOps, Finance, CS, and Analytics Engineers to deliver reliable, production-grade data for reporting and AI workflows.

Lead implementations of SimCorp Data Management Core, analyze back-office and IT data processes, design and configure solutions, run client workshops, advise on process improvements, contribute to product roadmap and knowledge sharing, and collaborate with international teams to ensure high data quality and lifecycle management for financial instruments.

Lead data governance for a major data platform project: define and enforce governance artifacts (access, metadata, quality, ownership), align SLAs and operational readiness, manage change and issues, enable stakeholders through training, and advise on report governance and compliance.

Lead and scale end-to-end data annotation operations: set quality standards, build and manage an in-house annotation team and vendors, translate research into annotation guidelines, implement QA systems, drive AI-assisted labeling, partner with ML/CV and product, and own metrics and reporting.

Lead people analytics by building end-to-end models and production data pipelines, designing dimensional models, and creating LLM/NLP solutions. Translate statistical outputs into executive-ready insights, develop automated dbt/Snowflake workflows and dashboards, partner with HR systems owners and the enterprise data office, and enforce data governance and privacy for People data to support strategic workforce decisions.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

Lead and build Burq's data and ML platform: own warehouse, ingestion, semantic layer, and BI; architect and ship forecasting, optimization, matching, and reliability models; implement feature pipelines, training/serving, and monitoring; drive AI agent initiatives; hire and grow a data/ML team; set governance, intake processes, and partner with product, engineering, and commercial stakeholders to align models with business impact.

As a Senior Associate in the Data + AI Advisory team, you'll execute data governance and MDM initiatives, collaborating with teams to define frameworks and solutions.

Lead analytics and operational insights for Customer Operations: define core metrics, build dashboards and forecasts, model churn/renewal risk, enable self-serve reporting, implement AI-enabled automation, and partner cross-functionally to drive retention, expansion, and support efficiency.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

Design, build, and scale IAM platform services and APIs for authentication, authorization, identity lifecycle, access governance, and compliance. Integrate identity providers and authorization systems, improve scalability and observability, design machine and service authentication, participate in architecture reviews, and mentor engineers.

Support vehicle profitability analysis by developing automated COP/CMP-I models, dashboards, and forecasts using Power BI, Excel, and data techniques (regression, scenario modeling). Translate analytics into pricing and incentive insights, partner with IT to improve data quality, and drive process automation and forecasting for budgeting and strategic initiatives.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.