Data Product Owner, Research

Sanofi•Toronto, ON

2d•CA$124,800 - CA$174,800•Onsite

About The Position

Sanofi is undergoing a significant digital transformation, with a focus on accelerating data transformation and adopting AI/ML solutions to enhance R&D, manufacturing, and commercial performance. The Data Platforms and Products Team within R&D Digital is crucial for developing and delivering Data and AI products for R&D use cases, aiming to democratize data and scale AI/ML capabilities. This role, Data Product Owner, Research, will lead the strategy, roadmap, and delivery of data products that support R&D portfolio management, enabling teams to plan, evaluate, and optimize the drug development pipeline. The position involves driving stakeholder alignment, influencing data architecture, and building data products such as data hubs, metadata lineage tools, timeline modeling, and analytics enablement. The company envisions an AI-first organization with versatile teams operating in cross-functional pods, utilizing a leading-edge tech stack, and offering world-class mentorship and training in machine learning.

Requirements

Master’s degree or higher in life sciences, computer science, data science, or a related field. Ph.D. or MBA is a strong plus.
8+ years of experience in data product management, operations, or digital product development in life sciences.
Strong familiarity with R&D management processes, systems, and use cases.
Proven leadership experience influencing cross-functional teams and driving digital or data transformation in R&D.
Ability to define product vision and strategy and translate that into team deliverables and stakeholder outcomes.
Excellent communication and executive presentation skills, including the ability to represent the organization at internal and external forums.
Proven track record of hiring, developing, and retaining top product talent.
Strong knowledge of Agile/Scrum methodologies, product management, and iterative product development.
Understanding of metadata management, data catalogs, data lineage, and cloud-native data architecture (e.g., AWS, Snowflake, Databricks).
Experience managing CI/CD pipelines and product releases for data infrastructure.
Experience working with product tools like Jira, Confluence, Miro, and enterprise data platforms.
A strong data-driven mindset, with the ability to balance innovation with compliance and operational excellence.

Nice To Haves

Ph.D. or MBA
Understanding of analytics, forecasting models, or program-level risk tracking is a strong asset.

Responsibilities

Define and own the data product strategy, enabling high-quality, harmonized, and accessible data to support strategic decision-making in R&D.
Partner with stakeholders to align product vision to business priorities and regulatory requirements.
Ensure the roadmap is scalable and flexible to meet global and therapeutic-area specific needs.
Lead quarterly and annual planning, prioritizing initiatives based on impact, resource capacity, and scientific value.
Bridge the gap between scientists and product teams to ensure that outcomes are aligned to business needs and value.
Gather and prioritize requirements from scientists, technical stakeholders, and cross-functional teams to define the “What” and “Why” of product development.
Oversee a suite of interconnected in silico fabric data products (e.g., program hierarchy models, timeline data APIs, asset metadata stores, risk modeling tools).
Oversee cross-product dependencies, ensuring interoperability, governance alignment, and compliance with data quality standards.
Ensure all products follow best practices in FAIR data principles, CI/CD delivery, and audit-readiness.
Build and manage a shared services model across product teams, including re-usable data assets, common pipeline components, and metadata catalogs.
Collaborate with Digital R&D platform leads, enterprise data governance teams, and AI/ML leaders to influence data infrastructure investments.
Partner with R&D Management, Strategy & Operations, and Finance teams to ensure in silico fabric data products meet real-world decision-making needs.
Cultivate a culture of accountability, agility, innovation, and user-centered thinking.
Promote knowledge sharing, collaboration, and continuous learning across product domains.
Ensure timely and high-quality delivery of data products in alignment with sprint plans and release milestones.
Champion agile product development and iterative delivery, balancing short-term execution with long-term product health.
Drive measurement of impact through business KPIs, data usage metrics, and stakeholder satisfaction.
Resolve escalated product or delivery risks, and coordinate mitigation strategies across internal and external teams.