Reference No. R2794590
Position Title: Product Owner - Research and Transversal AI,ML Workflows
Department: R&D Data Products and Platforms
Location: Toronto, Ontario
About the Job
Our Hubs are a crucial part of how we innovate, improving performance across every Sanofi department and providing a springboard for the amazing work we do. Build a career and you can be part of transforming our business while helping to change millions of lives.
At Sanofi, we're committed to providing the next-gen healthcare that patients and customers need. It's about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before. Join our R&D Data & AI Products and Platforms Team as a Data Product Owner and you can help make it happen.
Sanofi has recently embarked into a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.
The R&D Data & AI Products and Platforms Team is a key team within R&D Digital, focused on developing and delivering Data and AI products for R&D use cases. This team plays a critical role in pursuing broader democratization of data across R&D and providing the foundation to scale AI/ML, advanced analytics, and operational analytics capabilities.
We are looking for a Product Owner to lead the development of innovative software products supporting Scientific Workflow Engineering in AI/ML. This includes advanced machine learning-based (ML Ops) workflows, including generative AI for protein design, protein folding, and structural chemistry.
As the Product Owner, you will be responsible for collaborating with scientists and technical stakeholders, managing the full product lifecycle from gathering requirements to product delivery and continuous improvement. You will work closely with a dedicated scrum team composed of data engineers and full-stack platform engineers to deliver high-impact digital products that empower cutting-edge scientific research and innovation.
Our vision for digital, data analytics and AI
Join us on our journey in enabling Sanofi's Digital Transformation through becoming an AI first organization. This means:
AI Factory - Versatile Teams Operating in Cross Functional Pods: Utilizing digital and data resources to develop AI products, bringing data management, AI and product development skills to products, programs and projects to create an agile, fulfilling and meaningful work environment.
Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.
World Class Mentorship and Training: Working with renown leaders and academics in machine learning to further develop your skillsets.
We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people's lives. We're also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?
Main Responsibilities:
Product Ownership:
Lead the development and evolution of digital products that support bioinformatics workflows and ML operations, ensuring they meet scientific, research, and business objectives.
Own the product roadmap, defining clear and actionable goals that align with the strategic direction of the company and the needs of the scientific teams.
Bridge the gap between scientists and product teams to ensure that outcomes are aligned to business needs and value. The product owner will be a master coordinator, driver, and translator.
Gather and prioritize requirements from scientists, technical stakeholders, and cross-functional teams to define the 'What' and 'Why' of product development.
Collaboration & Stakeholder Management:
Work closely with scientists, data engineers, and platform engineers to ensure the product meets both scientific and technical requirements.
Collaborate with senior leaders and cross-functional teams (including R&D, technology, and operations) to ensure alignment and ensure the product strategy is supported by business cases and industry standards.
Product Delivery:
Oversee the agile product development process, ensuring smooth product delivery from initial conception to ongoing iterations.
Adept at mitigating risks and issues as they arise over the course of product delivery, along with reporting and providing regular product updates to broad forums.
Partner with the Scrum Master and delivery team to ensure timely and successful sprints, address challenges, and resolve any ambiguities.
Manage backlog prioritization, balancing short-term deliverables with long-term goals and breakthrough ideas.
Continuous Improvement:
Track the performance and impact of the product post-launch, gathering feedback to drive continuous improvements and enhancements.
Monitor user satisfaction, adoption, and scientific outcomes to ensure the product evolves to meet the needs of researchers and business goals.
Technical Leadership & Strategic Vision:
Bring a deep understanding of scientific workflows in bioinformatics and ML operations, particularly in areas like protein design, folding, and structural chemistry.
Stay up to date with industry trends, emerging technologies, and bring ideas and solutions to the business to address needs and drive maturity.
Inspire and lead a team of engineers by articulating a clear vision for the product and demonstrating the potential for innovative solutions.
About You
Key Functional Requirements & Qualifications:
Master's degree in computer science, bioinformatics, data science, or a related scientific field. Ph. D. or equivalent experience in relevant scientific domains is a plus.
5+ years in product management, preferably with experience in bioinformatics, life sciences, or AI/ML platforms.
Experience leading product development in scientific environments, particularly in areas like small molecule and large molecule research.
Familiarity with cloud environments such as AWS to build and deploy scientific and AI/ML workflows.
Strong understanding of machine learning operations (ML Ops), particularly in generative AI, protein design, protein folding, and structural chemistry.
Key Technical Requirements & Qualifications:
Comprehensive knowledge of Agile methodologies, including experience working in Scrum teams. <.