Senior Data Analyst - Manufacturing

ResMed (UK); Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

ResMed (UK) is seeking a Senior Manufacturing Data Analyst to translate operational data into actionable analytics across manufacturing value streams. You will collaborate with site leaders, engineers and frontline users to define questions, gather data and deliver practical dashboards and decision-support tools.

The role requires hands-on analytics, strong manufacturing knowledge and ability to communicate findings clearly to both operational and technical audiences, supporting predictive and

Qualifications

• Bachelor's degree in Engineering or related field; advanced degree preferred.
• 6+ years delivering analytics, automation or AI-enabled solutions in manufacturing or supply chain.
• Strong understanding of manufacturing value streams and improvement opportunities.
• Experience with ERP, MES, and OT data environments.
• Experience in cross-functional agile/project delivery teams.

Responsibilities

• Partner with value stream owners to define problems, questions and data needs.
• Analyze production, process, quality, downtime, cycle-time, labour data for loss drivers.
• Enable real-time visibility with part-level data, OEE, availability and quality loss diagnostics.
• Develop dashboards, reports and analytical models embedded in workflows.
• Work with data engineers, solution architects and data scientists on data pipelines.
• Support UAT, release readiness, adoption and feedback-driven improvements.

Skills

Analytics delivery

Automation

AI-enabled solutions

Manufacturing knowledge

Cross-functional teams

Education

Bachelor's degree in Engineering, Manufacturing, Supply Chain Management, Computer Science, Data Science, Information Systems, Business or related field

Advanced degree in Engineering, Data Science, Analytics, Manufacturing, Supply Chain or related discipline

Tools

ERP

MES

IoT data platforms

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.

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.

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 environment.