On - Lead - Technology Product Manager
Requirements
• 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.
Responsibilities
• 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.
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