Top Data Science Jobs in Toronto

Leads product strategy and development for Mastercard’s Business Identity solutions supporting agentic commerce. Translates strategic goals into roadmaps, gathers customer and stakeholder requirements, prioritizes features, and coordinates engineering, data science, legal, and commercialization teams. Manages product launches, lifecycle planning, performance tracking, and continuous improvement while advancing merchant verification, risk intelligence, fraud mitigation, regulatory compliance, and digital trust. Mentors product managers and drives measurable customer and market impact.

Leads product management for identity and token intelligence solutions that prevent fraud in digital payment ecosystems. Responsibilities include identifying customer and fraud use cases, defining product features, prioritizing roadmaps, analyzing product and model performance, coordinating with engineering and data science, and supporting commercialization through marketing and sales enablement.

Conduct research and develop innovative machine learning solutions for enterprise banking applications. The role provides AI/ML thought leadership, applies advanced techniques to generate business insights, collaborates with data and engineering teams, and leads research and development in an AI subfield. Responsibilities include designing analytic solutions, conducting research, publishing findings, mentoring colleagues, managing risk and governance, and partnering with business stakeholders.

Leads a team of Product Sales Specialists responsible for product adoption, cross-sell, expansion, pipeline, and revenue outcomes. Coaches consultative selling, manages forecasting and performance, develops scalable sales plays, and partners with Account Executives, Account Managers, Product, Marketing, Operations, Data Science, and Enablement. The role also engages in strategic seller opportunities, improves product expertise across sales teams, and builds repeatable commercial motions for Square’s products.

Leads strategic data analytics, translates complex analysis into business insights, develops data visualizations, and recommends solutions to senior stakeholders. Serves as a subject matter expert on data science, data mining, big data, and statistical modeling. Guides technical strategy, advises on business operations and risk, influences significant decisions, and manages team resources and work allocation.

Own the acquisition product roadmap and engineering priorities to drive durable user growth. Define target audiences and channel mix, build product-driven acquisition mechanics (referrals, growth loops), enable channel effectiveness (discoverability, search/AI readiness, integrations, tracking), test new acquisition tactics, and align product investment with Performance Marketing, SEO, Partnerships, and Brand while measuring long-term subscriber value.

Leads CIBC’s Insurance Decision Science team, setting technical standards for actuarial, statistical, data science, and AI-enabled methods. Oversees analytics supporting insurance pricing, profitability, growth, forecasting, portfolio performance, and strategic decisions. Builds capabilities, challenges assumptions, advises executives, manages talent strategy, and develops relationships across insurance, retail banking, technology, and analytics teams.

Lead data science initiatives for agentic AI products, partnering with data scientists, AI/ML engineers, and product managers. Build, deploy, validate, and optimize machine learning models using large-scale numeric and textual data. Design A/B tests, analyze telemetry, translate technical findings into business strategy, research emerging technologies, and develop talent while guiding enterprise-scale AI decisions.

Lead technical strategy and pre-sales engagement for large enterprise accounts, guiding customers through Databricks adoption and data-driven transformation. Build executive relationships, present technical value propositions, coordinate virtual teams, develop technical champions, align account strategies, and mentor colleagues. The role requires expertise in big data, data science, cloud, ML and AI use cases, plus production programming experience in Python, R, Scala, or Java.

Lead technical strategy and adoption of Databricks solutions for large financial services and insurance accounts. Partner with enterprise sales teams, executives, influencers, and technical resources to drive data and AI transformation, build technical champions, guide evaluations, and align solutions with business outcomes. The role requires expertise in big data, data science, cloud platforms, machine learning, programming, value selling, and technical leadership across global enterprise accounts.

Leads enterprise HR analytics and AI consulting engagements from discovery through delivery. Translates business challenges into scalable analytics solutions, manages senior client stakeholders, and guides cross-functional data science, data engineering, and business analyst teams. Oversees HR data transformation initiatives, advises on workforce metrics, supports embedding analytics into business processes, and identifies opportunities for solution pitches and account expansion.

Lead analytics consulting engagements for enterprise clients by translating business challenges into AI and analytics solutions. Define agentic AI requirements, workflows, and outcomes; oversee end-to-end delivery; collaborate with technical and global teams; manage stakeholders and projects; apply statistical and machine learning techniques; and help operationalize solutions that deliver measurable business value.

Develop enterprise customers’ automation strategies, identify and deploy high-value AI-enabled use cases, quantify ROI, and drive adoption, renewal, and expansion. Build executive and stakeholder relationships, advise on governance and scalable orchestration, coordinate internal and customer teams, interpret usage data, and create repeatable methodologies and playbooks for Zapier’s enterprise customer success program.

Own the vision, strategy, roadmap, requirements, KPIs, and go-to-market execution for insurance-focused data products. Collaborate with engineering and data science teams on products, proofs of concept, and demos; communicate progress to executives; and ensure compliance with BFS regulatory, risk, and compliance requirements.

Leads and develops a data science team, mentors scientists, and oversees production machine learning models for product features and internal business systems. Designs experimentation programs, partners with Engineering, Product, Design, and executives, and drives applied AI initiatives across scheduling, hiring, payroll, pricing, personalization, sales, and marketing.

Lead product strategy and market fit for CoCounsel Tax, Audit & Accounting across corporate customers. Research customer needs, prioritize the roadmap, define enterprise workflows, and shape MCP/API-based AI platform capabilities. Partner with engineering, data science, subject matter experts, marketing, sales, and operations to launch technically complex products, improve onboarding, support enterprise security and compliance, and enable corporate go-to-market efforts.

Supports onboarding of international research sites by mapping records to a LIMS schema, migrating legacy data, executing bulk imports and scheduled transfers, reconciling identifiers and vocabularies, monitoring data feeds, resolving failures, verifying data integrity, and training partner-site users. The role uses SQL, PostgreSQL, Python, and PHP for data transformation and supports scientific drug-discovery data integration.

Leads strategy and execution for large-scale data engineering and analytics programs. Coordinates engineering, data science, product, and business stakeholders; manages roadmaps, dependencies, milestones, risks, reporting, and delivery. Ensures data definitions, transformations, models, and downstream analytics remain accurate and fit for purpose while navigating complex, ambiguous initiatives involving multiple teams and partners.

Lead technical strategy and pre-sales engagement for major financial services and insurance accounts. Guide enterprise customers through data and AI transformation, drive Databricks adoption, build technical champions, present solutions to executives, and coordinate sales and technical teams. Apply expertise in big data, data science, cloud platforms, machine learning, and production programming to deliver business outcomes across large global accounts.

Lead Payments Data Science and Analytics for eBay Financial Services. Manage analysts, define analytics strategy and roadmaps, measure product performance, conduct A/B testing and causal inference, build predictive analytics and dashboards, and partner with Engineering, Product, and Business teams to drive cost savings, revenue growth, and product decisions.

Develop and deploy machine learning pipelines and advanced AI models for drug discovery using complex biomedical and DNA-Encoded Library datasets. Responsibilities include data preprocessing, predictive modeling, deep learning, exploratory analysis, visualization, MLOps, experiment tracking, and reproducible workflows. Collaborate with structural biologists, medicinal chemists, and bioinformaticians, communicate findings to diverse audiences, and evaluate emerging approaches for molecular property prediction and de novo drug design.

Leads Agile delivery across multiple teams or complex value streams, facilitating Scrum ceremonies, coaching teams, resolving impediments, managing dependencies and risks, and aligning stakeholders. The role oversees backlog and sprint goals, delivery metrics, release and change management, governance, reporting, and continuous improvement. Experience with analytics programs, cloud platforms, and tools such as Azure DevOps, Jira, Confluence, and Miro is valuable.

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.

Leads and mentors a data science team developing machine learning, AI, predictive, prescriptive, and generative AI solutions. Partners with business stakeholders to prioritize use cases, oversees model development and production deployment, and ensures governance, monitoring, documentation, explainability, fairness, and responsible AI standards. The role also communicates analytical insights, evaluates emerging technologies, manages team performance and resources, and supports enterprise risk, regulatory, and strategic initiatives.