Data Analyst – Process Engineering Molding Jr. Staff

We are looking for a Data Analyst to support the Process Engineering Molding team in analyzing production data, improving process efficiency, and enabling data-driven decision making, including support for New Product Introduction (NPI).

Key Responsibilities

• Create, maintain, and take full ownership of production reports (daily, weekly, monthly), ensuring accuracy, consistency, and timely delivery
• Collect, process, and analyze molding process data (cycle time, reject rate, downtime, etc.)
• Develop dashboards and visual reports to monitor production performance
• Translate data into clear insights and actionable recommendations
• Identify trends, issues, and improvement opportunities in molding processes
• Support root cause analysis for defects and inefficiencies in collaboration with engineering teams
• Support New Product Introduction (NPI) activities by analyzing trial data, monitoring process performance, and ensuring smooth product ramp-up
• Develop data monitoring systems to improve productivity and quality

Qualifications

• Bachelor’s degree in Industrial Engineering, Statistics, Mathematics, or related field
• 1–3 years of experience as a Data Analyst (fresh graduates with strong analytical skills are welcome)
• Basic understanding of manufacturing processes; experience in injection molding is a plus
• Proficient in: Advanced Microsoft Excel & Data visualization tools (Power BI, Tableau, or similar)
• Strong analytical thinking and problem-solving skills
• Able to handle and analyze large datasets
• Strong attention to detail, especially in reporting accuracy and consistency
• Responsible and disciplined in managing and delivering reports
• Good communication skills and ability to work cross-functionally
• Good command of English (written and spoken)

Preferred Qualifications (Nice to Have)

• Experience in plastic manufacturing or injection molding industry
• Experience supporting New Product Introduction (NPI) or product trial processes
• Knowledge of statistical tools such as SPC or DOE
• Understanding of Lean Manufacturing or Continuous Improvement methodologies
• Experience in developing structured, automated, and standardized reporting systems