Lead Data Scientist, Smart Manufacturing & Yield

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

Job summary

HOYA Electronics Singapore Pte Ltd is seeking a lead Data Scientist to build and scale data-driven capabilities across manufacturing operations, establishing the data science function, standards, and roadmap as the first data science hire in the region.

You will partner with process, equipment and IT teams to deploy predictive maintenance, yield optimization, demand forecasting, and process improvements, delivering ROI through measurable metrics and scalable MLOps capabilities.

Qualifications

• 5–8+ years of data science or ML experience; semiconductor/manufacturing preferred.
• Strong Python/R programming and ML frameworks.
• Experience with time-series data, predictive maintenance and process optimization.
• Ability to communicate across functions and manage stakeholders.

Responsibilities

• Define and execute data science strategy aligned with manufacturing goals.
• Build scalable data pipelines and production-grade ML models (MLOps).
• Lead data science practice, establish standards and roadmaps.
• Collaborate with process and equipment teams to drive adoption of insights.
• Deliver high-impact analytics across wafer fabrication, assembly and test.

Skills

Python

Machine Learning

Data Analysis

Statistical Modeling

Time-series analysis

Stakeholder communication

Problem solving

Communication

Cross-functional collaboration

Education

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or related field

Tools

TensorFlow

PyTorch

scikit-learn

SQL

ETL pipelines

Job description

HOYA Electronics Singapore Pte Ltd is seeking a lead Data Scientist to build and scale data-driven capabilities across manufacturing operations, establishing the data science function, standards, and roadmap as the first data science hire in the region.

You will partner with process, equipment and IT teams to deploy predictive maintenance, yield optimization, demand forecasting, and process improvements, delivering ROI through measurable metrics and scalable MLOps capabilities.