Data Analyst, Manufacturing (Manufacturing)

Location: Singapore, Singapore

Company

hirify.global develops healthcare products and solutions, with this role supporting manufacturing excellence and operational performance.

What you will do

• Analyze production, process, quality, downtime, cycle-time, labour, material-flow and cost data to identify loss drivers, trends, constraints, process variation and improvement opportunities.
• Extract, prepare, combine and validate manufacturing data using approved sources and methods, including ERP, MES, equipment, IoT, historian and similar operational technology data.
• Apply data profiling, descriptive statistics, segmentation, root-cause analysis, statistical process control and time-series analysis.
• Build and maintain dashboards, reports and visualizations; complete reconciliation, quality checks and test evidence before release.
• Support solution adoption through user feedback, guidance, training materials, standard work and reusable documentation.
• Work in cross-functional delivery squads, translating operational requirements into analytical outputs and communicating dependencies, risks and data limitations.

Requirements

• Bachelor’s degree in Engineering, Manufacturing, Supply Chain Management, Computer Science, Data Science, Information Systems, Business or a related field.
• 3+ years developing complex, cross-functional analytics, automation or AI-enabled solutions in manufacturing or supply chain environments.
• Understanding of manufacturing processes, value streams and operational improvement opportunities.
• 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 in cross-functional agile or project delivery teams, supporting solutions through requirements, testing, deployment and adoption.

Nice to have

• Advanced degree in Engineering, Data Science, Analytics, Manufacturing, Supply Chain or a related discipline.
• Experience in 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.

Culture & Benefits

• Challenging, supportive and inspiring workplace focused on excellence.
• Diverse and inclusive culture encouraging individual expression and innovative ideas.
• Commitment to responding to every applicant.