AI & Data Scientist for Semiconductor Manufacturing

onsemi; Carmona; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

onsemi is seeking a Data Scientist / AI professional to develop advanced analytics and AI solutions for semiconductor manufacturing operations. The role combines data science, AI, and manufacturing knowledge to enhance production performance and efficiency.

Responsibilities include building predictive/prescriptive models, data modeling, and collaborating with engineers and stakeholders to drive yield optimization and Industry 4.0 initiatives.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or related discipline.
• 5+ years of analytics, ML, or AI experience.
• Proficient in data modeling, ML, AI, and statistical analysis.
• Experience with large-scale structured and unstructured data.

Responsibilities

• Develop predictive and prescriptive analytics solutions for manufacturing processes.
• Design and implement machine learning and AI models.
• Build comprehensive data models supporting manufacturing analytics.
• Analyze production, process, quality, and equipment data.
• Collaborate with manufacturing engineers and business stakeholders.
• Support smart manufacturing and Industry 4.0 initiatives.
• Deliver insights to improve yield, productivity, and equipment performance.
• Present findings to technical and business audiences.

Skills

Data Modeling

Machine Learning

Artificial Intelligence

Statistical Analysis

Python

SQL

Education

Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, or related discipline

Tools

Azure

OCI

Snowflake

Job description

onsemi is seeking a Data Scientist / AI professional to develop advanced analytics and AI solutions for semiconductor manufacturing operations. The role combines data science, AI, and manufacturing knowledge to enhance production performance and efficiency.

Responsibilities include building predictive/prescriptive models, data modeling, and collaborating with engineers and stakeholders to drive yield optimization and Industry 4.0 initiatives.