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Added 4 mins ago
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- Full-time
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Manager Primary Health Care
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Rogers Communications

Product Owner

Toronto, ON, Canada

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Job details

Experience: 3+ years working in Data Science or AI/ML, with experience in Product Management, Portfolio Management, or Program Management.
Posting language: English
Posted: Oct 14, 2026

Original job description

We are committed to connecting Canadians through unique partnerships, our world-class network and content Canadians love - and our innovative team is growing. We are looking for dedicated team members to join our Corporate team who have a genuine passion for making positive impacts on customers and the communities where we live and work. We have a variety of business units with exciting and meaningful work waiting for you, including Communications, HR, Legal and Corporate Affairs, Supply Chain, Finance, and Real Estate. If you are considering your next step, we have exciting opportunities waiting for you. Come build a rewarding career at Rogers and be a driving force behind our success story!

Who we're looking for:
The Manager, Data Science Product Owner is responsible for the Portfolio & Product Management, managing the roadmap, prioritization, and lifecycle of Machine Learning (ML) models and model feature-store capabilities. Acting as the primary interface between business stakeholders and the Model Development & Strategy (MDS) team, this role translates business opportunities and requirements into a prioritized portfolio of data science and data capabilities. The role works closely with Data Scientists, Data Engineers, MLOps teams, and business partners to ensure initiatives are properly defined, prioritized, delivered, adopted, and continuously optimized throughout their lifecycle.

This role requires a strong understanding of the end-to-end machine learning lifecycle and the ability to balance business value, technical feasibility, delivery effort, and available capacity across a complex portfolio of initiatives.

What you'll do:

Portfolio Roadmap & Prioritization
- Own and maintain the roadmap and backlog for machine learning models and feature-store assets.
- Balance investment across new capability development, enhancement of existing assets, model retraining, and ongoing maintenance activities.
- Evaluate and prioritize competing requests based on business value, strategic objectives, delivery effort, dependencies, risks, and available capacity.
- Support portfolio planning activities and provide recommendations to Data Science leadership regarding priorities and sequencing.
Business Partnership & Demand Management
- Act as the primary liaison between business stakeholders and the MDS organization.
- Gather and assess demand from business teams and translate business problems into clearly defined use cases, requirements, expected business value, success metrics, and implementation needs.
- Facilitate intake, discovery, and requirements discussions to ensure initiatives are appropriately defined before entering the delivery pipeline.
- Build strong relationships with stakeholders to understand evolving business priorities and identify opportunities for new analytical and machine learning capabilities.
Delivery Coordination & Execution
- Coordinate end-to-end delivery across Data Science, Data Engineering, MLOps, and other teams responsible for developing and operationalizing solutions.
- Manage dependencies, delivery sequencing, risks, and cross-functional coordination across multiple concurrent initiatives.
- Partner with technical specialists to evaluate feasibility, implementation approaches, delivery effort, technical dependencies, and resource requirements.
- Facilitate planning, status reviews, and stakeholder updates to ensure successful execution and deployment.
Model & Feature Store Lifecycle Management
- Maintain visibility into the inventory, status, and health of production models and feature-store capabilities.
- Track assets throughout their lifecycle, including intake, development, validation, deployment, monitoring, enhancement, retraining, and retirement.
- Support governance reviews, lifecycle checkpoints, and model portfolio management activities.
- Ensure appropriate documentation, traceability, and portfolio reporting are maintained.
Adoption, Performance & Value Realization
- Track adoption, utilization, and business impact of delivered models and feature-store capabilities.
- Monitor asset performance and identify opportunities for optimization, reuse, consolidation, enhancement, or retirement.
- Support measurement and reporting of business outcomes and value realization.
- Prepare portfolio dashboards, performance reporting, and executive-ready summaries for leadership review.

What you bring:

3+ years working in Data Science or AI/ML, with experience in Product Management, Portfolio Management, or Program Management.
Strong understanding of the machine learning lifecycle, including feature engineering, model development, validation, deployment, monitoring, retraining, and retirement processes.
Experience working with Data Scientists, Data Engineers, MLOps teams, and business stakeholders.
Demonstrated ability to manage competing priorities and coordinate cross-functional initiatives.
Strong analytical, communication, stakeholder management, and facilitation skills.
Experience translating business requirements into actionable delivery plans.
Preferred
- Experience supporting machine learning, customer decisioning, marketing analytics, or AI product portfolios.
- Familiarity with feature stores, MLOps practices, model governance, and model lifecycle management.
- Experience with Databricks, Azure ML, Azure DevOps, Jira, or similar platforms.
- Telecommunications, marketing analytics, or customer analytics experience.
Success Measures
- Portfolio priorities are transparent, aligned, and effectively managed.
- Business demand is translated into a well-defined and actionable delivery pipeline.
- Models and feature-store capabilities are delivered efficiently and adopted by stakeholders.
- Portfolio health, lifecycle status, and business impact are consistently tracked and reported.
- Opportunities for enhancement, reuse, optimization, and retirement are proactively identified and executed.

What’s in it for you?
We believe in investing in our people and helping them reach their potential as valuable members
of our team. As part of our team, you’ll have access to a wide range of incredible resources, growth
opportunities, discounts, and perks, including:

Competitive salary & annual bonus.
Competitive & flexible health and dental benefits, pension plan, RRSP, TFSA, and Stock matching programs.
Discounts: Enjoy up to 50% off Rogers Services and Blue Jays Tickets, 25% off TSC items, and a 20% discount on all wireless accessories sold in Rogers stores.
Paid time off for volunteering.
Company matching contributions to charities you support.
Growth & Development Opportunities:
- Self-driven career development programs.
- Rogers First: priority in applying to internal roles of interest.
Wellness Programs:
- Employee & family assistance program.
- Virtual Healthcare.
- Cognitive Behavioural Therapy (CBT).
- Low or no-cost fitness membership.
Our commitment to diversity:
- An inclusive and diverse workplace where you can bring your whole self to work.

To protect our people, brand and assets, a pre-employment background check will be conducted. As part of our selection process, all candidates must clear a criminal background check. Additionally, a credit check and drivers abstract may be required depending on the role.

Schedule: Full time Shift: Day Length of Contract: Not Applicable (Regular Position) Work Location: 1 Mount Pleasant (083), Toronto, ON Travel Requirements: Up to 10% Background Check(s) Required: Canadian Criminal Record Check Posting Category/Function: Technology & Information Technology Requisition ID: 344128

To support career growth, collaboration, and high-performing teams, all Corporate Employees are expected to work onsite. We believe that in-person connection strengthens our culture and drives industry-leading performance.

At Rogers, we believe the key to a strong business, is a diverse workforce where equity and inclusion are core to making everyone feel like they belong. We do this by embracing our diversity, celebrating our different perspectives, and working towards creating environments that empower our people to bring their whole selves to work. Everyone who applies for a job will be considered. We recognize the business value in creating a workplace where each team member has the tools to reach their full potential by removing any barriers for equal participation. We work with our candidates who are experiencing a disability throughout the recruitment process to ensure that they have what they need to be at their best. Please reach out to our recruiters and hiring managers to begin a conversation about how we can ensure that you deliver your best work. You matter to us! For any questions, please visit the Recruitment Process FAQ.

Posting Notes: Corporate

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More about this job

Responsibilities

The Product Owner manages the roadmap, prioritization, and lifecycle of machine learning models and feature-store capabilities. They act as the primary liaison between business stakeholders and the technical teams to ensure initiatives are defined, delivered, and optimized.

Requirements

Candidates must have 3+ years of experience in Data Science or AI/ML with a background in product or program management. A strong understanding of the end-to-end machine learning lifecycle and experience working with cross-functional technical teams is required.

Skills

Product management
Portfolio management
Machine learning lifecycle
Data science
Stakeholder management
Feature engineering
Model development
MLOps
Data engineering
Strategic planning
Requirements gathering
Project coordination
Analytical skills
Communication
Facilitation

Benefits

Competitive salary
Annual bonus
Health benefits
Dental benefits
Pension plan
RRSP
TFSA
Stock matching programs
Employee discounts
Paid time off for volunteering
Charity matching
Career development programs
Employee and family assistance program
Virtual healthcare
Cognitive behavioural therapy
Fitness membership

Visa sponsorship

Not detected in the job text

Keywords

Product Owner
Data Science
Machine Learning
MLOps
Feature Store
Portfolio Management
Roadmap
Backlog
Stakeholder Management
Databricks
Azure ML
Azure DevOps
Jira
Marketing Analytics
Customer Analytics
Telecommunications
Model Governance
Lifecycle Management
Business Intelligence
Data Engineering

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