Senior Manager, Manufacturing AI & Analytics

About the role

The Senior Manager, Manufacturing AI and Analytics is a key delivery leader within ResMed's Manufacturing Excellence programme. The role implements AI, automation and analytics solutions across global manufacturing value streams to deliver measurable operational and financial outcomes. It leads multiple cross-functional squads and drives solutions from design through deployment, adoption, scaling and value realization. It is not a hands-on data science or engineering role.

Key responsibilities

• Own and manage the portfolio and roadmap for manufacturing AI and analytics solutions, partnering with Value Stream Owners, the Manufacturing Excellence PMO and transformation leaders on prioritization, feasibility and scalability.
• Lead multiple cross-functional squads to turn business and user needs into use cases, requirements, delivery plans and measures of success.
• Align capacity, sequencing and dependencies, track progress, risks and blockers, and guide solution and integration decisions with clear accountability and governance.
• Embed solutions into manufacturing workflows by involving leaders and users, and coordinate the process, role and capability changes needed for adoption.
• Help proven solutions scale across sites and value streams while balancing global standards with local needs, and promote reuse and capture implementation learning.
• Link delivery and adoption to operational and financial outcomes, track adoption and value indicators, and report results to senior stakeholders.

Required profile

• Bachelor's degree in Engineering, Manufacturing, Supply Chain Management, Computer Science, Data Science, Information Systems, Business or a related field; advanced degree preferred.
• Demonstrated experience leading complex, cross-functional delivery of analytics, automation or AI-enabled solutions in manufacturing or supply chain environments.
• Experience coordinating multiple delivery teams across business, process, data and technology disciplines.
• Strong understanding of manufacturing processes, value streams and operational improvement opportunities.
• Experience scaling digital, analytics, automation or AI solutions across sites, processes or value streams; Industry 4.0 or large-scale manufacturing transformation experience preferred.

Required skills

• Sufficient technical depth to assess solution feasibility, data readiness, systems integration, scalability and delivery risk, and to work with technical specialists.
• Experience with manufacturing data and technology environments such as ERP, MES, equipment or IoT data, historians or similar OT platforms.
• Delivery leadership, facilitation and stakeholder management, including driving adoption and influencing senior stakeholders.