Product Data Analyst and Quality Engineer

Asa Product Data Analyst and Quality Engineer trainee, you will gain exposure to product quality engineering activities with a focus on warranty data analysis, module-level testing, failure analysis, and AI-supported customer anomaly investigation.

Through on-the-job training, you will learn to use GenAI and analytical methods to support warranty PPM and warranty cost trend analysis, identify trends and anomalies, create dashboards to illustrate key insights, and participate in improvement discussions with the project team.

You will also gain practical experience using software tools, bench test setups, laboratory equipment, module schematics, and engineering documentation to support failure analysis, while learning structured problem-solving tools such as 8D and Diagnostic Trees under guidance from technical and cross-functional stakeholders.

EXPERIENCE/EDUCATION REQUIREMENTS:

• Degree in Electronic, Electrical, Computer Science, Data Analytics, or related Engineering discipline.
• Interest in learning and applying GenAI tools, data analysis, and dashboard visualization to support quality and warranty trend analysis.
• Basic understanding of electronic manufacturing, assembly, test processes, or product quality concepts.
• Basic exposure to schematic diagrams, electronic components, semiconductor devices, or laboratory test equipment is preferred.
• Analytical mindset with willingness to learn structured problem-solving methods such as 8D, Diagnostic Trees, troubleshooting, and root cause analysis.

FUNCTIONS:

• Apply GenAI tools to support analysis of warranty PPM and warranty cost trends, including identification of trends, anomalies, and incoming spikes from warranty data.
• Develop and use AI-supported tools and dashboards to visualize warranty trends, highlight key insights, and support data-driven improvement discussions.
• Conduct module-level testing and failure analysis on assigned product catalogs using software tools, bench test setups, laboratory equipment, module schematics, and engineering documentation.
• Apply failure investigation methodologies and root cause analysis techniques to troubleshoot product issues and support resolution with technical stakeholders.
• Use AI-supported approaches to strengthen customer anomaly investigation, productivity, and decision-making.
• Apply structured problem-solving tools, including 8D and Diagnostic Trees, to real business cases and customer anomaly investigations.
• Document investigation findings, prepare analysis reports, and present recommendations clearly to stakeholders.
• Collaborate with cross-functional project teams to identify improvement initiatives, corrective actions, and opportunities to improve quality performance.

Interpersonal:

• Demonstrate good working relationships within work group.
• Look for ways to collaborate and build teamwork with others.
• Demonstrate responsiveness and promptness in serving customer needs.
• Protect confidential information.
• Balance many priorities and competing demands effectively.
• Understand the business environment in which RA operates and works with global team supporting off office hours meetings as required.
• Understand the organization's mission and strategies.