The intern will work closely with field finance and sales team to:

• Conduct a comprehensive analysis of our current spares forecast process and identify areas for improvement.
• Research and evaluate various machine learning algorithms suitable for our specific needs.
• Develop a prototype machine learning model to predict spares demand based upon historical data and other relevant factors for a specific global account (TSMC and/or Samsung).
• Test and refine the model's performance, incorporating feedback from our team and stakeholders.
• Document the process and present findings to our team and management for further discussion and implementation.

Requirements:

• Currently enrolled in an undergraduate or graduate program in Computer Science, Data Science, Mathematics, Statistics, Economics or a related field.
• Solid understanding of machine learning concepts and techniques, including regression, classification, clustering, and time series analysis.
• Proficient in Python and R programming languages, with experience in machine learning libraries and frameworks
• Strong problem-solving skills and ability to think critically and creatively.
• Good communication and collaboration skills.

Duration: The internship is expected to last for one year, depending on the availability and performance of the candidate.
Location: Shanghai, China

Qualifications

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Certifications:

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Additional Information

Time Type:
Part time
Employee Type:
Intern / Student
Travel:
No
Relocation Eligible:
No
Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.