Key Responsibilities:

1.

Analyze wafer sort and final test data to identify trends, root causes and improvement opportunities.

2.

Develop and maintain Python scripts and SQL queries to automate data processing, extraction, and transformation.

3.

Build and enhance dashboards using Tableau to visualize yield, test time and failure analysis.

4.

Support and develop machine learning models for tasks such as wafermap clustering, failure pattern recognition and anomaly detection.

5.

Work with large datasets stored in Snowflake, optimize queries and dataflows for performance and scalability.

6.

Collaborate with engineering teams to define analytics requirements and deliver actionable insights.

7.

Explore and evaluate AI tools (eg NLP models, summarization tools) to help summarize issue found/filed by wafer sort and final test engineers.

8.

Document analytics workflows, code and dashboards to ensure knowledge sharing and maintainability

Qualifications:

•

Bachelor's degree in Electrical/Electronic Engineering, Computer Science, Data Analytics, or related field.

•

Proficient in Python and SQL, with experience using data libraries such as pandas, numpy, matplotlib and scikit-learn.

•

Hands-on experience with Snowflake for data analysis or pipeline development.

•

Familiar with data visualization tools such as Tableau, Power BI or other data visualization tools.

•

Strong problem-solving and analytical skills, with attention to detail.

•

Good communication and collaboration skills.