Job Description:

We are looking for a data-driven and detail-oriented Entry-Level Data Scientist to join our semiconductor engineering team. This role is ideal for recent graduates who are passionate in applying data science to solve complex challenges in product development, test optimization, quality assurance, and yield improvement. You will work closely with Product, Test, Quality, and Yield Engineers to analyze high-volume manufacturing and test data, develop predictive models, and uncover insights that drive process improvements and product reliability. This is a unique opportunity to contribute to cutting-edge semiconductor technologies through data science.

Key Responsibilities:

• Analyze wafer sort, final test, and inline process data to identify trends, anomalies, and root causes
• Build statistical and machine learning models to predict yield, detect outliers, and improve test coverage
• Develop dashboards and visualizations to monitor key metrics across product and test stages
• Collaborate with cross-functional engineering teams to translate data insights into actionable improvements
• Automate data pipelines and reporting tools to support continuous improvement initiatives
• Support quality investigations through data mining and correlation analysis
• Develop non-existent AI/ML solutions to solve problems
• You will have access to cloud compute resources (CPU, GPU)
• Training, guidance and coaching will be given

Requirements:

• Bachelor’s degree in Data Science, Electrical Engineering, Computer Science, Statistics, or a related field
• Strong foundation in statistics, data analysis, and machine learning
• Proficiency in Python or R, with experience using libraries such as pandas, NumPy, scikit-learn, and matplotlib
• Familiarity with SQL and working with large-scale databases
• Understanding of semiconductor manufacturing and test processes is a plus
• Experience with data visualization tools (e.g., Tableau, Power BI, or Plotly) is an advantage
• Ability to interpret complex datasets and communicate findings clearly to engineering teams
• Strong problem-solving skills, attention to detail, and a collaborative mindset
• Internship or academic project experience in manufacturing, electronics, or data analytics is a plus

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