Responsible for designing, developing, and maintaining business intelligence and analytics applications that embed product quality intelligence into key lifecycle quality decisions. Planned, organized, and coordinated data and reporting activities to transform manufacturing, test, and field information into actionable insights. Collaborates with product quality, engineering, reliability, test, supply chain, and field quality teams to monitor performance, detect early risk indicators, and support root cause analysis (RCA). Responsible for operationalizing quality KPIs (yield, defect rates, fallout, escapes, reliability indicators, and customer-reported failure trends) through standardized datasets, dashboards, and analytics-ready models. Additionally, proposes and contributes to advanced analytics and machine learning opportunities to improve quality prediction, classification, and anomaly detection.
- Design and deliver BI and analytics solutions providing visibility into product quality performance across the lifecycle.
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Translate manufacturing, test, supply chain, and field data into analytics-ready datasets through effective data modeling and data integration collaboration.
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Define, standardize, and operationalize product quality KPIs (yield, defect rates, fallout, escapes, reliability indicators, and customer failure trend metrics).
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Develop dashboards, reports, and visual analytics aligned with quality, engineering, and operations user needs.
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Proactively analyze trends and anomalies
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Partner with cross-functional teams
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Support root cause analysis (RCA) and systemic issue identification using structured data exploration.
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Collaborate with global data/development teams
