Strong foundation in statistical methods including SPC, DOE, sampling plans, process capability analysis, and measurement systems analysis. Proficiency in JMP and programming languages such as Python, R, or SQL. Experience in data analysis within semiconductor, MEMS, or high-volume manufacturing environments is preferred. Strong communication and stakeholder management skills, with the ability to translate complex analytics into practical manufacturing actions.
Four-year or Graduate Degree in Statistics, Data Science, Engineering, or a related discipline. Experience in semiconductor, MEMS, or advanced manufacturing is preferred. Candidates with strong applied analytics or AI experience, particularly in manufacturing environments, are highly valued.
Able to conduct data analysis and data engineering/modelling to prepare data for model training.
Develop and manage end-to-end AI pipelines, including data ingestion, preprocessing, embedding, model interaction, and output validation.
Collaborate with cross-functional teams (business users, IT, vendors) to ensure AI solutions align with operational needs and enterprise architecture.
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Excellent problem-solving skills to provide solution on technical problems.
Day-to-day liaison with other team members, bearing responsibility for ensuring that timings are met and those other developers are adhering to briefed requirements.
Ability to work in a variety of client settings and in a team-oriented, collaborative environment.
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