Lead Data Scientist for Smart Manufacturing & AI

HOYA Electronics; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

HOYA Electronics Singapore is seeking a lead Data Scientist to build and scale data-driven capabilities across our manufacturing operations. This foundational role delivers high-impact analytics and ML solutions while helping establish the data science function, standards, and roadmap across wafer fabrication, assembly, and test operations.

You will balance deep technical expertise with manufacturing domain awareness and stakeholder engagement across multiple fabs and business units.

Qualifications

• Bachelor's or Master's degree in a relevant field.
• 5-8+ years of data science or ML experience, preferably in manufacturing.
• Strong programming with Python and R.
• Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Expertise in data analysis, SPC, and DOE.
• Experience with time-series data and predictive maintenance is a plus.

Responsibilities

• Define and execute data science and AI strategy with process and engineering teams.
• Build scalable data pipelines for manufacturing, sensor, and tool data.
• Develop models for predictive maintenance, yield, and process optimization.
• Deliver production-grade ML models with monitoring and lifecycle management.
• Drive AI/ML adoption in manufacturing through internal platforms.

Skills

5-8+ years in data science or ML

Python, R programming

ML frameworks: scikit-learn, Tensor",

Education

Bachelor's or Master's degree in Data Science/Statistics/CS/Engineering

Tools

scikit-learn

TensorFlow

PyTorch

Job description

HOYA Electronics Singapore is seeking a lead Data Scientist to build and scale data-driven capabilities across our manufacturing operations. This foundational role delivers high-impact analytics and ML solutions while helping establish the data science function, standards, and roadmap across wafer fabrication, assembly, and test operations.

You will balance deep technical expertise with manufacturing domain awareness and stakeholder engagement across multiple fabs and business units.