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Data Science Product Manager Jobs in Toronto, ON

MasterCard

Director, Data Science

Toronto, ON · On-site

These models are designed to be production-ready and to power high-value capabilities that protect ... managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience.

Omnicom

Manager, Data Science

Toronto, ON · Hybrid

CA$90K - CA$100K/yr

Data Science and AI Position Summary We are hiring a Data Science Manager to lead project delivery across a range of data science engagements and serve as a key point of contact for clients. You will ...

CookUnity

Director, Data Science/ML

Toronto, ON

... managing data scientists or ML engineers * Proven track record building and deploying ML models in production , particularly in personalization, recommendation systems, or predictive modeling * Deep ...

CookUnity

Director, Data Science/ML

Toronto, ON

... managing data scientists or ML engineers * Proven track record building and deploying ML models in production , particularly in personalization, recommendation systems, or predictive modeling * Deep ...

Omnicom Media

Data Science Manager

Toronto, ON · Hybrid

CA$90K - CA$100K/yr

Position Summary We are hiring a Data Science Manager to lead project delivery across a range of data science engagements and serve as a key point of contact for clients. You will manage the day-to ...

Upshop

Product Manager

Mississauga, ON

CA$100K - CA$130K/yr

Product Manager Role Overview Upshop is seeking a Product Manager responsible for helping define ... Partner with engineering, UX, data science, revenue, and customer success teams * Support go-to ...

Capital One

Manager, Data Science

Toronto, ON · Hybrid

CA$173K - CA$197K/yr

161 Bay Street (93021), Canada, Toronto,Toronto, Ontario, Manager, Data Science About Capital One ... Designing and contributing to highly scalable data pipelines, tools, and products to enable the ...

Fig

Data Science Manager, Risk

Toronto, ON · On-site

... Science Manager, Risk to build and operationalize the models, data pipelines, and analytical ... Partner closely with Credit Strategy, Product, Growth, Finance, Engineering, and Data teams to ...

CIBC

Manager, Data Science

Toronto, ON · Hybrid

What You'll Be Doing The Manager, Data Science is responsible for providing analytics support to Business Lines and Finance team. This involves working with multiple stakeholders on data analysis ...

CIBC US

Manager, Data Science

Toronto, ON · Hybrid

What You'll Be Doing The Manager, Data Science is responsible for providing analytics support to Business Lines and Finance team. This involves working with multiple stakeholders on data analysis ...

Vangard, Inc.

AI/ML Product Manager

Toronto, ON · On-site

AI/ML Product Manager As an AI/ML Product Manager at Vanguard, you'll help shape how artificial ... Partner closely with engineering, data science, design, risk, legal, and business stakeholders to ...

Royal Bank of Canada

Product Manager

Toronto, ON · On-site

As a Product Manager on the MATA platform team, you will play a key role in bringing product ... You will collaborate with talented engineers, data scientists, and business stakeholders, with ...

Miqdigital

Product Manager

Toronto, ON · Hybrid

Drive product development with cross-functional teams including engineering, data science ... in a product management role * Experience working with engineering, data science and other ...

Varicent

Senior Product Manager - AI

Toronto, ON

Role Overview As a Senior Product Manager, AI Adoption & Customer Value , you will lead the 1-to-n ... Partner with Product Operations, Data Science, Engineering, Customer Success, and Go-to-Market ...

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All JobsData Science Product JobsData Science Product Manager JobsData Science Product Manager Jobs in Toronto, ON

Data Science Product Manager information

See Toronto, ON salary details

$26.7K

$99.2K

$163.2K

How much do data science product manager jobs pay per year?

As of Aug 30, 2026, the average yearly pay for data science product manager in Toronto, ON is $99,205.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,169.00 and $120,724.00 per year, depending on experience, location, and employer.

What is a Data Science Product Manager?

A Data Science Product Manager is a professional who bridges the gap between data science teams and business objectives by guiding the development of data-driven products. They work closely with data scientists, engineers, and stakeholders to define product vision, prioritize features, and ensure successful product delivery. Their role involves understanding both the technical aspects of machine learning and analytics as well as user needs and business strategy. This ensures that data-powered products are effective, user-focused, and aligned with organizational goals.

How does a Data Science Product Manager typically collaborate with data scientists and engineers during a product lifecycle?

A Data Science Product Manager plays a crucial role in bridging the gap between business objectives and technical teams. Throughout the product lifecycle, they work closely with data scientists to define project goals, prioritize features, and translate business needs into actionable data-driven solutions. They also coordinate with engineers to ensure the seamless integration of machine learning models into products, address technical constraints, and facilitate communication between cross-functional teams. This collaborative approach ensures that data science initiatives are both technically feasible and aligned with overall business strategy.

What are the key skills and qualifications needed to thrive as a Data Science Product Manager, and why are they important?

To thrive as a Data Science Product Manager, you need a strong background in product management, data analytics, and a foundational understanding of machine learning, often supported by a degree in a technical or quantitative field. Familiarity with tools like SQL, Python, JIRA, and knowledge of data platforms and agile methodologies is typically required. Excellent communication, strategic thinking, and the ability to bridge technical and non-technical teams are vital soft skills. These competencies ensure successful product development, effective stakeholder alignment, and the delivery of impactful data-driven solutions.

What is the difference between Data Science Product Manager vs Data Analyst?

AspectData Science Product ManagerData Analyst
Required credentialsBackground in data science, product management, or related fields; often requires experience with machine learning and data-driven product developmentTypically holds a degree in statistics, mathematics, or business; skills in data visualization and basic analytics
Work environmentCollaborates with product teams, data scientists, engineers; focuses on developing data products and strategiesWorks with business units to interpret data, generate reports, and support decision-making
Employer and industry usageUsed in tech companies, e-commerce, and organizations developing data-driven productsCommon across finance, marketing, healthcare, and business intelligence roles

The main difference is that Data Science Product Managers oversee the development of data products and strategies, requiring a blend of product management and data science skills. Data Analysts focus on interpreting data and generating insights to support business decisions. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Science Product Manager jobs in Toronto, ON?

For Data Science Product Manager jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Data Science Product Manager jobs in Toronto, ON look for?

The top searched job categories for Data Science Product Manager jobs in Toronto, ON are:

Data Science Product Manager jobs near you
Infographic showing various Data Science Product Manager job openings in Toronto, ON as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $99,205 per year, or $47.7 per hour.

Senior Data Product Manager, Data & Intelligence

Toronto, ON • Remote

NearSource
IT Services • 11 - 50 employees
Learn more about NearSourceexternal

Full-time

Posted 4 days ago

Job description

Job Title: Senior Data Product Manager, Data & Intelligence
Job Location: 100% Remote, Canada
Job Type: T4 Contract
Experience: 8+ Years
Rate: CAD 70 - 78 per hour

Role Summary: NearSource is looking for a Senior Data Product Manager, Data & Intelligence to translate strategic business priorities and stakeholder needs into scalable, trusted, and actionable enterprise data products.

The role operates at the intersection of business strategy, data, analytics, and engineering, driving product roadmaps, requirements, prioritization, and cross-functional delivery for complex data and intelligence initiatives.

Key Responsibilities

  • Translate strategic business goals and stakeholder needs into product roadmaps, product plans, epics, releases, and actionable requirements.
  • Lead product discovery with business stakeholders and technical teams to define user needs, use cases, workflows, and desired outcomes.
  • Own product prioritization based on customer value, strategic alignment, dependencies, technical feasibility, and implementation effort.
  • Partner with Engineering Managers, Technical Leads, Data Engineers, Analysts, Data Scientists, Business Intelligence teams, and Data Governance specialists throughout the product lifecycle.
  • Manage product backlogs, requirements, dependencies, risks, acceptance criteria, release readiness, and stakeholder communications.
  • Ensure technical solutions remain aligned with defined business and user outcomes.
  • Drive alignment across business and technical stakeholders by communicating priorities, decisions, trade-offs, risks, and progress.
  • Establish feedback loops and success measures to improve product quality, adoption, scalability, and business impact.
  • Identify opportunities for standardization, reuse, simplification, and automation to reduce one-off solutions.
  • Translate ambiguous strategic objectives into clear, prioritized, and executable product plans for technical delivery teams.
  • Drive delivery of trusted, reusable, and scalable data and intelligence products that support Go-to-Market decision-making.

Must-Have Skills

  • 8+ Years of experience as a Data Product Manager, Technical Product Manager, Product Manager, or similar role working with technically complex products.
  • Strong experience in strategic planning and translating business objectives into actionable product roadmaps.
  • Strong stakeholder management experience across business and technical teams.
  • Hands-on experience with analytics and data science products.
  • Experience with product discovery, roadmap development, prioritization, and requirements definition.
  • Experience managing epics, releases, product backlogs, dependencies, and acceptance criteria in an Agile environment.
  • Proven ability to translate ambiguous business problems and stakeholder needs into clear and executable product plans.
  • Experience partnering closely with engineering or technical development teams.
  • Working knowledge of data models, data pipelines, APIs, data quality, data governance, analytical platforms, or enterprise data products.
  • Strong written and verbal communication skills, including the ability to communicate complex technical concepts to non-technical stakeholders.

Nice-to-Have Skills

  • Experience with Customer Data Governance or Master Data Management.
  • Experience with Customer 360, customer identity, entity resolution, account hierarchies, match/merge, or deduplication.
  • Experience with third-party data ingestion, data enrichment, data quality, reconciliation, or exception management.
  • Experience with policy-driven data workflows, controls, audibility, or automation.
  • Experience with enterprise analytical data platforms, data warehouses, or lake house environments.
  • Experience with governed datasets, shared metrics, data definitions, or semantic consistency.
  • Experience with BI products, dashboard consolidation, migration, or rationalization.
  • Experience with embedded analytics or intelligence within enterprise applications.
  • Experience with predictive analytics, machine learning, recommendation, scoring, or decision-support products.
  • Experience with model explainability, experimentation, or hypothesis-driven product development.
  • Experience operationalizing analytical models and insights within business workflows.
  • Experience delivering intelligence or analytics through CRM platforms such as Salesforce.
  • Experience working in a complex, globally distributed enterprise environment.

Relevant Data Product Experience

Candidates should demonstrate meaningful experience in at least one of the following areas:

  • Customer Data Governance: Master Data Management, Customer 360, customer identity, entity resolution, account hierarchies, data quality, governance, reconciliation, and automated controls.
  • Customer Intelligence at Scale: Enterprise data and analytics platforms, governed datasets, shared metrics, data enrichment, product-ionized intelligence, BI products, embedded analytics, and AI-enabled data experiences.
  • Strategic Data Research and Data Science Products: Predictive analytics, machine learning, propensity and recommendation models, scoring products, model explainability, experimentation, and operationalized analytical insights.

Apply now, or share your resume with salary expectations at careers@nearsource.ca. Thank you for considering a career with us! Once you submit your application, our Talent Acquisition team will review your resume thoroughly. If there's a strong match, we'll reach out to discuss your experience, role details, benefits, compensation, and next steps. While we strive for transparency, we may not be able to respond to every applicant due to high volume, but we genuinely appreciate your time and interest.

About NearSource: NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives.

Equal Opportunity: NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.