Top Data Jobs in Toronto

Own audience or measurement products for Fetch’s monetization business, from problem framing through delivery. Build predictive models, datasets, population inferences, and causal measurement studies using receipt, partner, panel, survey, and contextual data. Partner with Product, Engineering, Sales, and GTM to productionize analyses, communicate methods and limitations to customers, and improve products using campaign outcomes, holdouts, and fresh data.

Own the data science strategy, analytical roadmap, and experimentation for ranking and relevance. Partner with engineering, product, commercial, and offer teams to improve advertiser outcomes, user value, retention, and marketplace economics. Design rigorous experiments and observational analyses, quantify incremental business impact, establish KPI frameworks and trade-off guardrails, influence launch and investment decisions, mentor colleagues, and build reusable analytical methods using large-scale data systems.

Owns the roadmap and product strategy for private markets, shareholder, and deals financial data. Responsibilities include identifying content gaps, defining requirements and PRDs, improving data quality and discoverability, collaborating with platform, engineering, design, and go-to-market teams, conducting QA, and driving adoption among financial analysts, investment bankers, and corporate development professionals.

Own the product roadmap for surfacing financial data through search, screening, and agentic capabilities. Define requirements, PRDs, and prioritization; collaborate with engineering, design, data platform, AI/ML, and go-to-market teams; and lead feature development from discovery through launch. Improve content structure, tagging, indexing, ranking, search relevance, screening precision, and agentic retrieval reliability for financial analysts, bankers, and corporate development users.

Supports data extraction, management, quality assurance, cleaning, validation, harmonization, statistical and qualitative analysis, and public health program evaluation. Develops analytic datasets and contributes to technical memoranda, reports, presentations, tables, and figures. Analyzes implementation measures and mixed-methods data, interprets findings, and recommends program improvements. Requires collaboration with government and public health stakeholders, use of Microsoft Office and CDC administrative systems, and the ability to obtain and maintain required customer clearance.

Leads GTM data governance, CRM processes, territory and ownership workflows, AI and automation enablement, and MaintainX’s GTM integration into Autodesk. Oversees data quality analysts, defines systems requirements, manages cross-functional programs, establishes AI standards, drives field adoption, and partners with sales, marketing, revenue operations, enablement, engineering, and executive stakeholders to improve productivity and integration outcomes.

Lead design and build scalable data architectures, ETL pipelines, ingestion and data quality frameworks. Collaborate with cross-functional teams, enforce data governance, analyze data for insights, mentor junior engineers, and serve as the technical authority on data engineering best practices.

Own and evolve Clutch’s end-to-end data platform, including scalable warehouse architecture, production ELT pipelines, analytics data models, quality monitoring, observability, governance, and DevOps practices. Partner with analysts, data scientists, and business stakeholders to support decision-making and financial services initiatives. Mentor engineers, improve technical standards, and use AI to accelerate development.

Leads the design, deployment, automation, and operation of secure enterprise cloud platforms across AWS and Azure. Builds Terraform infrastructure modules, CI/CD pipelines, and cloud data lake platforms while supporting Kubernetes, GitOps, security controls, governance, monitoring, compliance, reliability, and cost optimization. Collaborates with security teams, participates in audits, and promotes platform engineering best practices across development teams.

Design, build, and scale backend data services, APIs, microservices, distributed systems, and high-volume data pipelines. Optimize PostgreSQL and Oracle databases, improve reliability and performance across regions, diagnose complex production issues, and mentor engineers. Partner with DBA and SRE teams while providing hands-on technical leadership and owning services end to end.

Design, build, deploy, and optimize scalable, high-performance data platform components supporting analytics and machine learning. Responsibilities include distributed streaming infrastructure, API and system design, code and design reviews, performance tuning, production debugging, cross-functional collaboration, and mentoring engineers. The role works with technologies such as Kinesis, Flink, Elasticsearch, Snowflake, and distributed cloud systems.

Leads advanced data analysis, develops dashboards, KPIs, and analytical models, and translates business problems into data-driven solutions. Works with complex datasets using Databricks, SQL, Python, BI tools, and cloud data platforms. Partners with engineering and governance teams, promotes analytics standards, mentors analysts, and communicates insights to stakeholders. Supports strategic decisions through descriptive, predictive, and prescriptive analytics.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.

Lead electrical design for hyperscale, colocation, and mission-critical data centers. Develop medium- and low-voltage distribution, critical and backup power systems, resilient electrical architectures, load calculations, power-system studies, grounding, and protection solutions. Coordinate multidisciplinary designs, support construction and commissioning, collaborate with clients and stakeholders, mentor engineers, and contribute to proposals and technical presentations.

Design and integrate automation, monitoring, PLC, SCADA, BAS, and power-monitoring systems for hyperscale and mission-critical data centers. Develop control sequences, system diagrams, network architectures, specifications, and technical documentation. Coordinate HVAC, electrical, instrumentation, control-panel, and cabling interfaces. Support design reviews, construction services, commissioning, testing, cybersecurity requirements, and technical issue resolution.

Lead mechanical design for hyperscale, colocation, and mission-critical data centers. Design HVAC, cooling, heat-rejection, chilled-water, and resilient mechanical systems; perform heat-load calculations, airflow studies, capacity planning, and CFD analysis. Prepare technical documentation, coordinate multidisciplinary teams, support construction and commissioning, collaborate with clients and vendors, mentor engineers, and contribute to proposals and technical presentations.

Own NimbleRx’s end-to-end data platform, including ingestion, transformation, storage, querying, access, batch and streaming pipelines, warehouse modeling, security, compliance, and reliability. Optimize PostgreSQL and Java/Spring services, investigate infrastructure issues, create self-service documentation and tooling, apply AI to data workflows, and mentor engineers and analysts. The role partners broadly across product, engineering, analytics, and operations while driving the platform roadmap.

Owns end-to-end GTM and Finance analytics, including data extraction, strategic analysis, dashboards, metric definitions, and actionable recommendations. The role improves operational efficiency, enables self-service reporting, maintains trusted data assets, uses AI to accelerate analytical workflows, mentors analysts, and helps shape the analytics roadmap. It requires strong SQL, BI expertise, SaaS metrics knowledge, cross-functional influence, and experience with financial or go-to-market reporting.

Develop and deploy machine learning and statistical models for Commercial Auto Pricing, claims prediction, customer optimization, and automation. Responsibilities include transforming large datasets into insights, partnering with Pricing, managing the full model lifecycle, monitoring model performance, maintaining data science tools, improving reproducibility, and communicating recommendations to technical and non-technical stakeholders.

Design, develop and maintain data controls and governance for Financial Crime & Risk Management systems. Lead complex data initiatives, perform data profiling, root cause analysis, troubleshoot data pipelines, automate processes, integrate databases with analytics platforms, and collaborate globally to ensure data integrity for payments and transaction monitoring.

Develop, test, implement, document, and support data and AI products. Translate business requirements into technical solutions, contribute to designs, build reusable frameworks and automation, perform regression testing, resolve production issues through root-cause analysis, and improve delivery and deployment processes. The role requires experience with data engineering, ETL/ELT, cloud platforms, structured and unstructured data, AI concepts, GenAI, prompt engineering, RAG, Agile delivery, and JIRA.

Tenure-stream Associate or Full Professor conducting high-impact research in data science computation, including computational inference, optimization, randomized numerical methods, sampling, simulation, and scalable algorithms for high-dimensional problems. The role includes teaching, publishing in leading journals, mentoring students, contributing to the department’s strengths, and fostering equity, diversity, inclusion, and collegial learning environments.

Conduct research advancing theoretical and methodological foundations of computation in data science, including sampling, simulation, computational inference, optimization, randomized numerical methods, and scalable algorithms. Teach and mentor students, publish high-quality research, present at conferences, pursue research excellence, and contribute to inclusive and collegial learning environments.

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.