Job opportunity
Manager Data Science Product Owner
Rogers Communications, Inc.
Manage machine learning product portfolios at Rogers in Toronto, using roadmap ownership and stakeholder management to guide data science delivery.
The Manager, Data Science Product Owner oversees product and portfolio management for machine learning models and feature-store capabilities. You will translate business opportunities into prioritized use cases, requirements, success metrics, and implementation needs. The role connects business stakeholders with Data Scientists, Data Engineers, and MLOps teams throughout delivery and lifecycle management.
Key Responsibilities:
Own roadmaps and backlogs for models and feature-store assets
Prioritize requests using value, risks, dependencies, and capacity
Coordinate delivery across data and technical teams
Track model and feature-store lifecycle health
Report adoption, performance, and business impact
Requirements:
Three or more years in Data Science or AI/ML
Product, portfolio, or program management experience
Understanding of end-to-end machine learning lifecycle processes
Experience with Data Scientists, Data Engineers, and MLOps teams
Strong analytical, communication, facilitation, and stakeholder management skills
Guide Rogers machine learning portfolios through prioritization, delivery, governance, adoption, and continuous lifecycle optimization in Toronto.
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Apply on source site The Manager, Data Science Product Owner oversees product and portfolio management for machine learning models and feature-store capabilities. You will translate business opportunities into prioritized use cases, requirements, success metrics, and implementation needs. The role connects business stakeholders with Data Scientists, Data Engineers, and MLOps teams throughout delivery and lifecycle management.
Key Responsibilities:
Own roadmaps and backlogs for models and feature-store assets
Prioritize requests using value, risks, dependencies, and capacity
Coordinate delivery across data and technical teams
Track model and feature-store lifecycle health
Report adoption, performance, and business impact
Requirements:
Three or more years in Data Science or AI/ML
Product, portfolio, or program management experience
Understanding of end-to-end machine learning lifecycle processes
Experience with Data Scientists, Data Engineers, and MLOps teams
Strong analytical, communication, facilitation, and stakeholder management skills
Guide Rogers machine learning portfolios through prioritization, delivery, governance, adoption, and continuous lifecycle optimization in Toronto.
#J-18808-Ljbffr