Data Scientist

Job Details

: The Advanced Packaging Technology and Manufacturing (APTM) Yield Systems Organization is seeking a curious, thoughtful, and highly motivated Data Scientist with strong analytical capabilities and excellent communication skills. In this role, you will collaborate with yield analysts, engineers, and business partners to identify manufacturing yield challenges and translate them into scalable, data-driven system solutions that improve operational efficiency and product quality. The ideal candidate combines expertise in data science, automation, AI/ML, computer vision, and software development with a passion for solving complex manufacturing problems. You will play a key role in developing dynamic solutions that enhance yield performance, reduce manual effort, and strengthen APTM's overall technical capabilities.

. • Design, develop, and deploy scalable data science solutions that address yield-related challenges across advanced packaging manufacturing operations. • Create automated workflows and data pipelines that improve efficiency, accuracy, and decision-making. • Apply machine learning, artificial intelligence, statistical analysis, and computer vision techniques to identify patterns, detect anomalies, and drive yield improvements. • Develop and maintain software tools, dashboards, and applications that provide actionable insights to manufacturing teams. • Leverage manufacturing and fabrication (fab) data to generate dynamic, real-time solutions that enhance operational performance. • Collaborate across multidisciplinary teams to implement and support production-ready systems. • Communicate technical findings, recommendations, and project outcomes effectively to both technical and non-technical audiences. • Continuously evaluate emerging technologies and methodologies to improve APTM's yield analysis and manufacturing capabilities. Behavioral Traits • Excellent communication and collaboration skills to influence cross-functional stakeholders, and tolerance to ambiguity for quickly changing environments. • Proactive and self-driven with minimal supervision.