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Tier-1 brand, metro location, and broad ML/big-data skill requirements increase candidate competition.
Core ML and data engineering skills transfer across industries, though semiconductor/manufacturing experience is preferred.
Extensive mandatory ML, big-data, and software skill requirements imply strict technical filtering.
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Analyze and apply machine learning techniques on large-scale industrial manufacturing data (terabytes to petabytes).
Develop statistical models, feature extraction, and supervised/unsupervised/semi-supervised learning for data insights.
Extract and cleanse data from various databases using SQL and automate analyses with strong software development skills.
Experience with data science or machine learning in an industrial or manufacturing context (specific years not stated).
Proficiency in Python and/or R; knowledge of SQL databases (Teradata or others); experience with big data tools like Hadoop (Hive, Spark).
Skills in machine learning frameworks and statistical software, including Tensorflow and scripting for automation.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling large and diverse datasets including time-series and image data with changing distributions.
Comfortable working with advanced AI concepts such as agentic AI, statistical modeling, and semi-supervised learning.
Familiarity with manufacturing execution systems (MES) or semiconductor industry experience is a plus but not mandatory.