Job Summary
The Senior Manager, Manufacturing AI and Analytics is a key delivery leader within ResMed’s Manufacturing Excellence programme, responsible for implementing AI, automation and analytics solutions across global manufacturing value streams to deliver measurable operational and financial outcomes.
Leading multiple cross-functional squads, the role translates agreed priorities into coordinated execution and drives solutions from design through deployment, adoption, scaling and value realization.
Success requires strong manufacturing knowledge, complex delivery leadership and sufficient technical depth to guide decisions and mobilize specialist teams. This is not a hands-on data science or engineering role.
Let’s talk about Responsibilities
Solution Portfolio and Multi-Squad Delivery
• Own and manage the portfolio and integrated 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 translate business and user needs into clear use cases, requirements, delivery plans and measures of success.
• Align capacity, sequencing and dependencies; maintain visibility of progress, risks and blockers; and enable timely resolution or escalation.
• Guide practical solution and integration decisions, supported by clear accountability, consistent governance and effective delivery practices.
Operational Adoption
• Embed solutions into manufacturing workflows, decisions and ways of working by involving leaders and users throughout delivery.
• Coordinate the process, role and capability changes required for adoption, and address barriers to sustained use.
Global Scaling and Reuse
• Enable proven solutions to scale across relevant sites, processes and value streams while balancing global standards with legitimate local needs.
• Promote reuse, capture implementation learning and apply it to future deployments.
Value Realization
• Connect delivery and adoption to agreed operational and financial outcomes in partnership with Value Stream Owners and the Manufacturing Excellence PMO.
• Track adoption and value indicators, communicate outcomes to senior stakeholders, and surface gaps between technical completion and realised value.
Let’s talk about Qualifications and Experience
• 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 or squads across business, process, data and technology disciplines.
• Strong understanding of manufacturing processes, value streams and operational improvement opportunities.
• Sufficient technical depth to assess solution feasibility, data readiness, systems integration, scalability and delivery risk, and to work effectively with technical specialists.
• Experience with manufacturing data and technology environments such as ERP, MES, equipment or IoT data, historians or similar operational technology platforms.
• Strong delivery leadership, facilitation and stakeholder management skills, including driving adoption and influencing senior stakeholders.
• Experience scaling digital, analytics, automation or AI solutions across sites, processes or value streams; Industry 4.0 or large-scale manufacturing transformation experience preferred.
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