Top Data Jobs in Toronto

Develop and lead predictive, prescriptive, customer lifetime value, and machine learning models using complex financial and customer datasets. Partner with business, product, marketing, finance, and technology stakeholders to identify opportunities, deliver actionable insights, monitor model performance, and ensure regulatory compliance. The role also supports portfolio optimization, customer behavior analysis, model refinement, and responsible data science initiatives.

The Senior Marketing Analytics Lead will oversee analytics projects, translate data into insights, influence marketing strategies, and mentor junior team members.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

Develop and enhance Grafana data source plugins integrating third-party services and databases. Support plugin reliability and operations in Grafana Cloud, integrate data sources with agentic workflows, improve engineering processes, assist with customer escalations, and collaborate across the Grafana Division. The role requires strong Golang and TypeScript skills, Kubernetes and microservices experience, robust software development practices, and participation in on-call and SRE operations.

Build and deploy end-to-end statistical and machine learning solutions for clients and internal delivery teams. Responsibilities include scoping ambiguous problems, analyzing operational challenges, prototyping AI workflows, translating messy data and real-world constraints into scalable solutions, iterating with stakeholders, and developing reusable tooling and infrastructure. The role combines hands-on data science with technical consulting and requires communication with technical and non-technical stakeholders.

Lead end-to-end data science and machine learning projects, from scoping ambiguous client problems through production deployment. Build and evaluate statistical and ML models, analyze large datasets, run experiments, collaborate with engineers, create reusable tooling, communicate findings to diverse stakeholders, and mentor data scientists. The role combines hands-on data science with technical consulting and requires occasional customer on-call support.

Design and build scalable backend systems, APIs, data models, event-driven services, experimentation platforms, and personalization systems. Partner with Product, Data Science, Analytics, and Design teams to support customer acquisition and engagement. Establish secure, observable, high-performance engineering practices, mentor junior engineers, and participate in monitoring, on-call, and operational support.

Analyze product usage and telemetry data to identify trends, opportunities, and product improvements. Partner with Product Analytics, Data Science, and product teams to define success metrics and measurement plans. Build dashboards, reports, and self-service analyses using SQL and analytics tools, validate telemetry and data quality, and communicate findings through written analyses, presentations, and recommendations.

Leads North American indirect tax requirements and global tax data governance for an SAP S/4HANA transformation. Oversees U.S. and Canadian tax processes, tax determination, reporting, reconciliations, data standards, tax technology integrations, testing, deployment, audit readiness, and compliance. Partners across Tax, Finance, IT, Master Data, Analytics, Procurement, Supply Chain, and Shared Services to improve tax data quality and establish scalable global operating models.

Design, build, operate, and improve production data pipelines using Airflow, BigQuery, and GCP. Develop scalable data models, backend APIs, dashboards, and AI-powered workflows that transform documents into structured customer-facing intelligence. Implement LLM and agentic systems with retrieval, tool calling, evaluation, quality controls, and production safeguards. Collaborate with analysts, product teams, and stakeholders while independently solving ambiguous engineering problems.

Supports Odoo ERP master data management, data cleansing, validation, imports, sales order entry, and product record creation. Reviews engineering documents, develops structured datasets, documents procedures, and collaborates with engineering, operations, customer service, and business teams. The role also contributes to process improvement through AI tools, automation, scripting, and workflow enhancements.

Leads complex data science and advanced analytics initiatives to support business decisions. Oversees data mining, feature engineering, data quality, predictive modeling, segmentation, and model deployment. Develops programming for data preparation and model management, creates visualizations and executive presentations, establishes modeling guidelines, supports documentation and training, and improves data management tools. Acts as a subject matter expert and advisor while coordinating stakeholders and translating business needs into analytical solutions.

Oversee enterprise data quality and pipeline health across Airflow, dbt, Microsoft Fabric, SYNQ, and Power BI. Translate business rules into quality checks, monitor alerts, coordinate issue resolution, manage thresholds and lineage, and maintain audit evidence supporting SOC 1 controls. The role also supports controlled overrides, manual file ingestion, documentation, stakeholder coordination, and reporting-impact analysis while partnering with data governance, engineering, analytics, risk, controls, and audit teams.

Design electrical systems for hyperscale, colocation, and mission-critical data centers across North America. Responsibilities include electrical calculations, equipment sizing, drawings, one-line diagrams, specifications, code compliance, multidisciplinary coordination, design reviews, and construction-phase support. The role requires knowledge of Canadian electrical and building codes, resilient power infrastructure, and collaboration with clients, contractors, vendors, and utilities.

Lead applications systems analysis and development for Big Data platforms. Partner with management to define enhancements, resolve complex issues, enforce coding/testing standards, coach mid-level developers, and ensure compliance and risk management.

As a Product Manager, you'll lead product vision and strategy, utilizing customer insights and technology to create innovative solutions while collaborating with multiple teams.

Lead experimentation, causal analysis, and product analytics for eBay’s Seller Experience organization. Partner with Product and Engineering leaders to shape strategy, identify seller growth opportunities, and translate complex questions into actionable insights. Build reusable experimentation frameworks, data models, monitoring, and self-serve analytics tools, including AI-powered agents. Mentor junior data scientists and drive high standards for data quality, instrumentation, and measurement reliability.

Develop and validate machine learning and statistical models for consumer credit risk, fraud, portfolio management, IFRS 9 forecasting, and borrower behavior. Build explainable predictive models, automate analytical processes, identify quality data sources, document methodologies, and translate complex findings into actionable business insights. The role partners with cross-functional teams and balances model performance, interpretability, scalability, and commercial impact.

Own the technical direction, development, reliability, and migration of Faire’s data infrastructure. Build CDC and streaming ingestion pipelines from production databases through Kafka into Iceberg on S3, operate Airflow and Fivetran, and implement data contracts, quality checks, SLAs, and observability. Lead cross-team initiatives, mentor engineers, manage incidents and on-call responsibilities, and partner with data scientists, analysts, and engineering teams to deliver dependable analytical data platforms.

Evaluate AI model outputs, conduct audit-based reviews, identify patterns and failure modes, apply and improve evaluation guidelines, and document actionable findings. The role requires native-level Marathi, strong English, structured writing, GenAI safety knowledge, critical thinking, and comfort making judgment calls in ambiguous situations. Associates collaborate with leads and stakeholders, participate in calibrations, and help refine quality standards. This is a full-time, one-year, 100% onsite contract role in specified U.S. cities.

Evaluate AI model outputs, audit data and model behavior, identify edge cases and failure modes, apply and improve evaluation guidelines, communicate performance trends, participate in calibration discussions, and document actionable findings. The role requires native-level Tamil, strong English and writing skills, critical judgment, attention to detail, and familiarity with GenAI safety considerations. This is a full-time, one-year, 100% onsite contract position.

Analyze data and experiments, build metrics, dashboards, reports, pipelines, and data assets, and deliver actionable recommendations. The intern will assess product and business impacts through analytics and A/B testing, collaborate with multidisciplinary teams, communicate findings, and present work to stakeholders while learning from mentors.

Conduct statistical analysis, machine learning, predictive modeling, causal inference, experimentation, and time-series forecasting. Build scalable data pipelines, dashboards, reports, and production models using Python or R, SQL, and Spark. Analyze complex datasets, identify patterns and anomalies, optimize model performance, generate actionable recommendations, and present findings to data science and partner teams. The intern will collaborate with multidisciplinary stakeholders and work on fraud, losses, and financial crime problems.

Lead the architecture and hands-on delivery of end-to-end Azure data platforms, including ingestion, transformation, lakehouse modeling, analytics, APIs, and activation. Build batch and streaming pipelines with Microsoft Fabric, Azure Data Factory, Databricks, Python, PySpark, and SQL. Implement governance, security, CI/CD, MCP and agentic AI integrations, while troubleshooting production systems. Mentor engineers, advise client stakeholders, contribute to presales, and establish reusable engineering standards.

Analyze General Motors’ social data to measure campaign performance, audience sentiment, brand health, and business impact. Produce recurring reports, dashboards, and campaign presentations; evaluate paid social content; conduct social listening; identify trends and risks; and provide data-backed recommendations for content calendars, posting cadence, and creative formats. The role requires collaboration with agency and client teams and native fluency in French and English with knowledge of Quebec culture.