Senior Data Analyst - Manufacturing

547 ResMed Asia Pte. Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ResMed Inc. is seeking a Senior Manufacturing Data Analyst to translate manufacturing data into actionable insights and practical analytics solutions.

The role partners with leaders, engineers and data specialists to drive measurable operational and financial outcomes across value streams. Responsibilities include building dashboards, conducting time-series analyses and enabling near-real-time performance visibility.

Qualifications

• Bachelor’s degree in Engineering, Manufacturing, Supply Chain Management, Computer Science, Data Science, Information Systems, Business or related field; advanced degree preferred.
• 6+ years delivering analytics, automation or AI-enabled solutions in manufacturing or supply chain contexts.
• Strong understanding of manufacturing processes, value streams and continuous-improvement opportunities.

Responsibilities

• Collaborate with value stream owners to define problems, hypotheses, and data requirements.
• Develop dashboards, reports, and analytical models to support decision-making.
• Provide near-real-time manufacturing visibility including OEE diagnostics.
• Work with data engineers and OT/IT teams to define data pipelines and integration needs.
• Drive adoption, training and iterative improvement of analytics solutions.

Skills

Data analytics

Manufacturing data

Cross-functional collaboration

Continuous improvement

Statistical methods

Education

Bachelor’s degree in Engineering

Bachelor’s degree in Manufacturing

Bachelor’s degree in Supply Chain Management

Bachelor’s degree in Computer Science

Data Science / Analytics advanced degree (preferred)

Tools

ERP systems

MES systems

IoT data platforms

Industrial historians

Job description

Senior Manufacturing Data Analyst The Senior Manufacturing Data Analyst is a key delivery role within ResMed’s Manufacturing Excellence Program, responsible for analysing manufacturing data and developing practical analytics solutions that support measurable operational and financial outcomes across manufacturing value streams. The role works closely with manufacturing leaders, engineers, technicians, operators, data and technology specialists to translate operational problems into clear analytical questions, data requirements, insights, dashboards and decision-support tools. It supports solutions from discovery and data validation through development, deployment, adoption and ongoing improvement. Success requires strong manufacturing and continuous-improvement knowledge, hands‑on analytical capability and the ability to communicate findings clearly to both operational and technical audiences. The role will work across equipment, process, quality, labour and material‑flow data as well as supporting predictive and prescriptive analytics in partnership with data science and engineering specialists.

Let’s talk about Responsibilities

Manufacturing Data Products and Insights Partner with value stream owners, site teams, engineers and frontline users to define manufacturing problems, analytical questions, hypotheses, measures of success and data requirements. Analyse production, process, quality, downtime, cycle‑time, labour, material‑flow and cost data to identify loss drivers, trends, constraints, process drift and improvement opportunities. Enable near‑real‑time manufacturing performance visibility, including part‑level production data, OEE and performance, availability and quality loss diagnostics. Apply appropriate analytical methods including data profiling, descriptive statistics, correlation, segmentation, root‑cause analysis, statistical process control and time‑series analysis. Translate complex analysis into practical operational insights, clear recommendations and prioritised actions. Develop, test and maintain dashboards, reports, analytical models and decision‑support tools that are reliable, user‑centred and embedded in manufacturing workflows. Create clear metric definitions, calculation logic, data‑quality checks and documentation so that outputs are trusted, repeatable and scalable. Work with data engineers, solution architects, OT/IT teams and data scientists to define data pipelines, integration needs and fit‑for‑purpose analytical solutions. Support user acceptance testing, release readiness, training and adoption, and use feedback to improve the solution after deployment. Operational Adoption Embed solutions into manufacturing workflows, decisions and ways of working by involving leaders and users throughout delivery. Support and drive the process, role and capability changes required for adoption, and address barriers to sustained use. 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. Stakeholder Engagement and Delivery Communicate progress, findings, risks and data limitations clearly to manufacturing leaders, subject‑matter experts and programme stakeholders. Plan and manage assigned analysis and delivery activities, dependencies and milestones within cross‑functional squads. Facilitate working sessions that connect operational knowledge with data evidence and ensure recommendations are practical for the manufacturing environment. Build analytical capability in operational teams through coaching, documentation and simple self‑service tools where appropriate.

Let’s talk about Qualifications and Experience Required

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. 6+ years developing complex, cross‑functional delivery of analytics, automation or AI‑enabled solutions in manufacturing or supply chain environments. 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. Experience working in cross‑functional agile or project delivery teams and supporting solutions through requirements, testing, deployment and adoption. Preferred Qualifications and Experience Advanced degree in Engineering, Data Science, Analytics, Manufacturing, Supply Chain or a related discipline. Experience within Industry 4.0, smart manufacturing or large‑scale manufacturing transformation environments. Exposure to predictive or prescriptive analytics and experience building AI, data science or advanced analytics solutions. Experience supporting manufacturing excellence, Lean, Six Sigma or similar continuous‑improvement programmes. #LI-APAC Joining us is more than saying “yes” to making the world a healthier place. It’s discovering a career that’s challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, We commit to respond to every applicant. Resmed (NYSE:RMD, ASX: RMD) creates life‑changing health technologies that people love. We’re relentlessly committed to pioneering innovative technology to empower millions of people in more than 140 countries to live happier, healthier lives. Our AI‑powered digital health solutions, cloud‑connected devices and intelligent software make home healthcare more personalized, accessible and effective. Ultimately, Resmed envisions a world where every person can achieve their full potential through better sleep and breathing, with care delivered in their own home. Learn more about how we’re redefining sleep health at Resmed.com and follow @Resmed.