Lead Technical Product Manager, Operations AI & Data
The Product Management Technology team is the digital backbone of On's product creation engine. We are a team of strategic product leaders who partner with core business functions—from R&D and Design to Sourcing and Supply Chain—to build the platforms and systems that power On's growth.
Our mission is to create a seamless, intelligent, and efficient digital ecosystem that enables our teams to design and deliver the next generation of revolutionary products. We are internal entrepreneurs, deeply embedded in the business, who identify complex challenges and build elegant, scalable solutions.
As a member of our team, you will have a unique opportunity to drive significant transformation and make a tangible impact on the future of one of the world's most exciting brands.
The Role
At On, our supply chain is the backbone of our global operation. We are looking for a visionary Lead Technical Product Manager to spearhead the next evolution of our supply chain by harnessing the power of Artificial Intelligence and data.
In this leadership role, you will be the bridge between our complex operational challenges and cutting-edge data solutions. You will be responsible for identifying high-impact opportunities where data, AI and automation can revolutionize our planning, logistics, and decision-making processes. Your expertise will be in understanding the business, the data, and the possibilities of AI to define a compelling product vision and guide our AI, data and engineering teams to build solutions that deliver immense value.
As a Lead, you will also play a key role in mentoring other product managers and shaping the product culture within the team.
What You'll Do
- Own the Data & AI Product Vision: Develop and champion a clear product strategy and roadmap for Data & AI-driven initiatives within the supply chain domain.
- Identify Opportunities: Collaborate closely and build relationships with supply chain stakeholders to deeply understand their processes, data challenges, and automation pain points.
- Translate Problems into Solutions: Convert ambiguous business problems into well-defined product requirements, user stories, and specifications for our data science and engineering teams to drive measurable value.
- Prioritize for Impact: Create and manage a data-driven product backlog, prioritizing features and initiatives that deliver the highest value to the business.
- Define Success: Establish and monitor key performance indicators (KPIs) to measure the effectiveness and impact of your AI/data products, in partnership with analytics.
- Bridge the Gap: Serve as the primary liaison between business leaders, supply chain operators, data scientists, and engineers, ensuring alignment and clear communication across all teams.
What You'll Bring
- Leadership Experience: Proven experience as a Technical Product Manager, with a demonstrated history of leading significant products or initiatives from concept to launch.
- Supply Chain Acumen: Strong experience with supply chain data and a solid understanding of core supply chain principles (e.g., demand forecasting, inventory management, logistics).
- AI/Data Fluency: You have a basic familiarity with AI and machine learning concepts and, most importantly, a gift for translating business needs into data-driven solutions. You don't need to be an AI expert, but you must be adept at partnering with engineers and data scientists who are.
- Analytical mindset: You are able to creatively identify the right success metrics and analyses that will provide key insight into product functionality.
- Technical Aptitude: You are comfortable in a technical environment and capable of holding your own in discussions about data models, APIs, and system architecture.
- Strategic Problem-Solver: You excel at breaking down large, complex problems into actionable steps and have a strategic mindset to see the bigger picture.
- Exceptional Communication: You have an outstanding ability to communicate complex ideas clearly and effectively to both technical and non-technical audiences.