Fault Detection & Classification (FDC) Data Science Engineer

About Samsung Austin Semiconductor
Samsung is a world leader in advanced semiconductor technology, founded on the belief that the pursuit of excellence creates a better world. At Samsung Austin Semiconductor, we are Innovating Today to Power the Devices of Tomorrow.

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Position Summary

Samsung Austin Semiconductor is seeking a highly skilled and experienced Data Scientist Engineer to lead the development and implementation of the Fault Detection and Classification (FDC) system. This individual will have a strong background in data science, machine learning, and experience working in the semiconductor industry. The ideal candidate will be responsible for managing the FDC system's evolution and integration with other factory systems and processes, while driving continuous improvement through data-driven decision making.

The Fault Detection & Classification (FDC) System Engineer is a crucial role in maintaining the efficiency and productivity of an advanced semiconductor fabrication factory. This role is responsible for owning and overseeing the development and implementation of cutting-edge FDC systems, ensuring optimal equipment monitoring and performance.

Role and Responsibilities

Here’s What You’ll Be Responsible For:

• Lead the development, testing, and deployment of AI and data-driven solutions for the Fault Detection & Classification system, specifically for early detection and analysis of process/equipment anomalies.

• Own and oversee the development, implementation, and maintenance of the FDC system.

• Manage the system's evolution and integration with other factory systems and processes.

• Coordinate with cross-functional teams to optimize the FDC system for overall factory performance.

• Drive continuous improvement of the FDC system through data-driven decision making.

• Analyze data and trends to identify areas for improvement and implementation of system updates.

• Collaborate with data scientists and engineers to develop and deploy new models and methods for fault detection and classification.

• Develop and implement FDC methods and systems that meet the business needs of tier-1 foundries.

Skills and Qualifications

Here's what you'll need:

• Bachelor's degree or higher in Data Science, Machine Learning, Computer Science, Engineering, or a related field.

• 7+ years of experience in data science, machine learning, or a relevant field, preferably in the semiconductor industry.

• 5+ years of FDC experience desired.

The current base salary range for this role is between $106,000 - $174,500. Individual base pay rates will depend on factors including duties, work location, education, skills, qualifications and experience. Total compensation for this position will include a competitive benefits package and may include participation in company incentive compensation programs, which are based on factors to include organizational and individual performance.

Total Rewards
At Samsung Austin Semiconductor, base pay is just one part of our total compensation package. The base compensation for this role will depend on education, experience, skills, and location.

We offer a comprehensive benefits package, including:

• Medical, dental, and vision insurance
• Life insurance and 401(k) matching with immediate vesting
• Onsite café(s) and workout facilities
• Paid maternity and paternity leave
• Paid time off (PTO) + 2 personal holidays and 10 regular holidays
• Wellness incentives and MORE
  
  

Eligible full-time employees (salaried or hourly) may also receive MBO bonuses based on company, division, and individual performance.

All positions at Samsung Austin Semiconductor are full-time on-site.

U.S. Export Control
This role may require access to information subject to U.S. export control laws. Applicants must be authorized to access such information or eligible for government authorization.

Trade Secrets
By submitting an application, you agree not to disclose to Samsung or induce or encourage Samsung to use any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

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