ESSENTIAL DUTIES AND RESPONSIBILITIES:
- Identify, develop, and deploy AI use cases within AlMg Substrate manufacturing, targeting yield improvement, defect reduction, and equipment downtime minimization across Plate, Wash, and Polish processes.
- Build predictive and prescriptive models using available internal AI tools on manufacturing process data extracted from MES, ERP, and IoT/sensor sources.
- Apply statistical analysis techniques including SPC, DOE, Cpk analysis, hypothesis testing, and multivariate analysis to uncover KPIV-KPOV relationships in substrate manufacturing processes.
- Develop and maintain end-to-end(Substrate-Media-HDD) analytics pipelines - from data extraction and preparation through model training, validation, and production deployment.
- Create self-serve data dashboards and automated reports using Spotfire to support real-time Cpk, Yield, and SPC monitoring for the manufacturing line.
- Support AI-driven root cause analysis for quality excursions, reducing manual investigation cycle time.
- Provide engineering support for Substrate manufacturing process issues, applying data science tools to accelerate root cause identification and corrective action deployment.
- Collaborate cross-functionally with Process, Quality, Test/FA, and Metrology teams to integrate analytics capabilities into existing engineering workflows.
- Provide engineering support for Substrate manufacturing process issues, applying data science tools to accelerate root cause identification and corrective action deployment.
This position is part of our Early Career program at WD. Our Early Career program is designed to support individuals beginning their professional career by providing the foundational training through a structured onboarding, mentorship, and development curriculum.
