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Intel Fall Recruiting Season Data Science Engineer United States, Arizona, Phoenix 994863445
Yesterday
Data Science engineers' responsibilities include (but are not limited to):
- Provides process development direction throughout the whole lifecycle of a technology node by identifying root cause yield limiters.
- Performs statistical analysis, develops visualizations and presentations to construct accurate process development roadmaps that drive technology yield milestones.
- Develops methods, processes, and systems to consolidate and analyze diverse big data sources, establishing optimal methodologies for defect-mode understanding and yield modeling, leading to accurate yield Pareto construction and process roadmap definition.
- Organizes, interprets, and structures insights from fab process, defect, and electrical data and detects data anomalies and drives process changes for yield enhancement.
- Extracts insights from structured and unstructured data by quickly synthesizing large volumes of data, and applying statistics, machine learning and coding techniques.
- Develops systems to transform complex experimental and manufacturing data into yield improvement actions using knowledge of product design and test features.
- Ensures manufacturability over process and product design through thorough analysis of process and spec corners and works with design to resolve yield issues before manufacturing ramp.
- Executes new product introductions, enables design-technology co-optimization, and participates in design of experiments in factory task forces.
- Creates cross-functional collaborations across organizations to debug yield limiters in design, test, and process development areas.
- Develops tools, multivariate algorithms, and methodologies to perform high-volume data analysis to identify root cause yield limiters and identify key process changes to advance yield improvement.
- Performs fault isolation and failure analysis to determine the root cause of failures by evaluating the electrical characteristics of the components using various tools and techniques such as ATE testing, DFx software tools, optical probing, logic/circuit simulation, and emulation, probing, and layout study.
- Develops measurement recipes to provide quick and accurate feedback on product integrity, helping resolve issues with yield or product quality impact.
- Develops and hardens equipment capable of meeting operational and capability needs for leading edge logic node.
See for more details.
You must possess the minimum qualifications below to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. The experience listed below may be obtained through schoolwork, classes and project work, internships, military training, and/or work experience.
Minimum Qualifications:
- Masters or PhD degree in Computer Science, Physics, Chemical Engineering, Electrical Engineering
- Statistics Coursework, Statistical Process Control (SPC) or Design of Experiments (DOE) principles, and engineering analysis tools.
Preferred Qualifications:
6+ months of experience in one of the following:
- Experience in advanced node semiconductor industry in yield analysis and data science
- Experience in big data analysis and machine learning.
- Experience in in program languages and big data to develop a new analysis method and algorithms using large amount of fab data.
- Experience in GAA (Gate-All-Around) technology architecture.
- Experience in new semiconductor technology development.
- Experience with Device Physics and overall FinFET process flow.
- Data analysis skills with demonstrated ability to construct clear data-based problem statements.
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