Data Scientist

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Description

About the Role We are seeking a data-driven and detail-oriented Entry-Level Data Scientist to join our semiconductor engineering team. This role is perfect for recent graduates eager to apply data science to solve complex challenges in product development, test optimization, quality assurance, and yield improvement. You will collaborate with Product, Test, Quality, and Yield Engineers to analyse 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 advanced analytics and AI. Key Responsibilities Analyse 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. Innovate and develop AI/ML solutions for non-standard problems. Utilize cloud compute resources (CPU, GPU) for large-scale data processing. Receive training, guidance, and mentorship to accelerate your career growth . Requirements Bachelor’s degree in Data Science, Electrical Engineering, Computer Science, Statistics, or 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, matplotlib. Familiarity with SQL and working with large-scale databases. Understanding of semiconductor manufacturing and test processes is a plus. , Tableau, Power BI, 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. Preferred Skills (Added Advantage) Knowledge of Generative AI concepts and applications. Familiarity with Large Language Models (LLMs) and their integration into data workflows. Exposure to cloud platforms (AWS, Azure, etc) and big data frameworks.

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