About the Role
We are seeking an early‑career Data Scientist to apply AI/ML and Generative AI in semiconductor engineering. You will work with engineering teams to build ML models and GenAI‑powered analytics, automation, and decision‑support solutions on large‑scale manufacturing and test data.
Key Responsibilities
Apply statistical analysis and ML techniques to wafer sort, final test, and inline process data
Explore and develop AI/ML and Generative AI use cases, including LLM‑assisted analytics and automation
Design dashboards and visualizations to communicate AI‑driven insights to engineering teams
Automate data pipelines, model workflows, and reporting
Leverage cloud platforms and compute (CPU/GPU) for scalable data processing and model training
Qualifications
Bachelor’s or master’s degree in data science, Engineering, Computer Science, Statistics, or related field
1–2 years of applied experience in data science, ML, or AI‑driven projects
Strong foundation in machine learning, statistics, and data analysis
Proficient in Python or R (pandas, NumPy, scikit‑learn, etc.)
Working knowledge of SQL and large datasets
Familiarity with Generative AI concepts, LLMs, or prompt‑based workflows
Exposure to cloud platforms (AWS, Azure, or similar) and big data tools is a plus
Strong analytical thinking, problem‑solving, and communication skills
More information about NXP in Malaysia...
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We anticipate tomorrow’s needs—navigating a changing world by bringing together technology's brightest minds to build game-changing solutions that propel us forward.
NXP Semiconductors N.V. (NASDAQ: NXPI) is the trusted partner for innovative solutions in the automotive, industrial & IoT, mobile, and communications infrastructure markets. NXP's "Brighter Together" approach combines leading-edge technology with pioneering people to develop system solutions that make the connected world better, safer, and more secure. The company has operations in more than 30 countries and posted revenue of $12.61 billion in 2024. Find out more at www.nxp.com.
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