Process Data Analytics Engineer

Key Responsibilities

• Perform statistical analysis and interpret results to support manufacturing and engineering process improvement. 
• Partner closely with process engineers as an embedded analytics resource to investigate process behavior, document performance, and identify opportunities to reduce variability and improve control. 
• Prepare, clean, and organize data for analysis, including basic transformation and structuring of data from multiple sources. 
• Analyze existing manufacturing and quality datasets, with emphasis on MES data and part quality data from measurement systems. 
• Apply appropriate statistical methods to solve process and quality problems and to support hypothesis-driven investigations. 
• Develop dashboards, reports, and visualizations to communicate process performance and analytical findings to stakeholders. 
• Contribute to advance analytics solutions in machine learning, AI, and computer vision 
• Support APAC teams in leveraging data more effectively to monitor processes, identify trends, and enable data-driven decision-making. 
• Contribute to the development of standardized reporting and analytics approaches across sites and teams where appropriate. 
• Collaborate with cross-functional partners in engineering, manufacturing, quality, and other functions to understand needs and deliver practical analytical solutions. 
• Train and coach stakeholders on data usage, reporting tools, and interpretation of analytics results to build organizational capability. 
• Deliver value in environments where problems may be loosely defined and data may be incomplete, requiring initiative, sound judgment, and attention to detail. 

Required Qualifications

• Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science, Industrial Engineering, or a related technical discipline. 
• Approximately 3+ years of relevant experience in data analytics, statistical analysis, manufacturing analytics, process engineering analytics, or a related field. 
• Strong knowledge of statistics, data analysis, and analytical problem solving. 
• Strong SQL skills for data extraction, transformation, and analysis. 
• Strong Python skills for data analysis, visualization, and related workflows. 
• Experience creating data visualizations, dashboards, and reports to support decision making. 
• Ability to work effectively with manufacturing and quality data. 
• Ability to prepare, clean, and structure data for analysis. 
• Basic knowledge of data engineering concepts and data workflows. 
• Strong written and verbal communication skills in English. 
• Ability to explain analytical findings clearly to technical and non-technical stakeholders. 
• High attention to detail and strong organizational skills. 

Preferred Skills

• Direct manufacturing experience strongly preferred. 
• Experience with Databricks strongly preferred. 
• Experience with Power BI for dashboarding and reporting. 
• Experience with JMP for statistical analysis and visualization. 
• Familiarity with machine learning methods and their practical application in business or manufacturing settings. 
• Familiarity with LLMs, AI tools, or emerging analytics technologies. 
• Understanding of statistical process control (SPC), variation reduction, and manufacturing performance metrics. 
• Experience integrating or analyzing data from MES, quality systems, and measurement equipment. 
• Understanding of manufacturing processes and industrial data systems. 

Soft Skills

• Strong collaborator who can work closely with process engineers and cross functional teams to solve problems. 
• Self-motivated and able to work independently with limited direction. 
• Comfortable operating in ambiguous environments and defining a path forward. 
• Able to train, coach, and influence others in the use of analytics and data-driven thinking. 
• Strong communication and presentation skills, including the ability to work effectively across countries, teams, and cultures within APAC. 
• Detail oriented, with a strong focus on accuracy, data integrity, and follow-through.