We are seeking a skilled HDD data Analyst to help us leverage data to drive product development and optimization. This role involves analyzing component-level and HDD data to enhance our engineering processes and product performance. The ideal candidate will possess exceptional analytical abilities, a strong understanding of the physics of magnetic recording, and a passion for improving products through data-driven insights. Additionally, you will investigate and understand product issues and build physics-based and machine-learning models to predict and optimize product performance.ESSENTIAL DUTIES AND RESPONSIBILITIES Data Analysis: Collect, analyze, and interpret data from various sources, including component tests and HDD product evaluations, to identify trends, correlations, and areas for improvement.Product Optimization:  Utilize data-driven insights to recommend and implement changes in product design and development, aiming to enhance performance, reliability, and overall quality.Investigation: Investigate and diagnose product issues by analyzing data patterns and anomalies and understanding their root causes to inform product improvements.Model Building: Develop and implement physics-based models to simulate and predict product behavior and create machine-learning models to enhance predictive accuracy and optimization.Collaboration: Work closely with engineering teams to understand product requirements and development challenges, providing data-driven solutions and recommendations.Reporting: Develop and present detailed reports and visualizations to communicate findings, trends, and actionable insights to stakeholders at all levels.Continuous Improvement: Stay updated with the latest advancements in data analysis, machine learning, and physics-based modeling, applying these techniques to improve product development processes.Research: Apply knowledge of the physics of magnetism to interpret data related to magnetic components and systems, ensuring accurate analysis and application in product development.
