Data Analysis & Anomaly Detection: Perform exploratory data analysis (EDA) on semiconductor manufacturing data, including wafer fabrication, yield, and defect rates. Identify anomalies and outliers in semiconductor production data, suggesting corrective actions to improve yield. Model Development & Feature Engineering: Develop predictive models using machine learning techniques (such as regression, classification, and clustering) to optimize manufacturing processes and improve product quality. Extract relevant features from raw data, considering factors like material properties, process parameters, and environmental conditions. Visualization: Create clear and informative visualizations to communicate findings and insights to stakeholders. IoT: Work with enablement sensor data collection from edge devices as well as management of data pipelines. Collaboration: Work closely with engineers, physicists, and domain experts to understand semiconductor processes and translate business requirements into data-driven solutions Continuous Improvement: Stay up to date with industry trends, research advancements, and emerging technologies in data science and semiconductor manufacturing.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees