Data Scientist

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A global semiconductor company based in Singapore is seeking a skilled Data Scientist to join their Smart Manufacturing and AI team. This role focuses on developing digital twin solutions by applying advanced analytics, machine learning, and simulation technologies. The ideal candidate will have proficiency in Python, R, SQL, and experience with machine learning frameworks, particularly in the context of semiconductor manufacturing processes. You will collaborate with cross-functional teams to enhance productivity and efficiency.

Qualifications

• Strong proficiency in Python, R, SQL, and data engineering.
• Experience with machine learning frameworks and simulation tools.
• Knowledge of semiconductor manufacturing processes and fab operations.

Responsibilities

• Work with teams to create digital twins of fabs.
• Build and maintain data-driven models for fab processes.
• Develop algorithms for predictive maintenance and throughput optimization.
• Use simulation tools to run scenarios for layout changes.

Skills

Python

R

SQL

machine learning frameworks (TensorFlow, PyTorch)

data engineering

semiconductor manufacturing processes

IoT data pipelines

cloud platforms (AWS, Azure)

3D modeling and visualization tools (Omniverse, Unity)

Tools

NVIDIA Omniverse

Job description

Overview

As a Data scientist at Micron Technology, Inc., you will report to the Smart Manufacturing and Artificial Intelligence organization. The team defines, develops, and delivers end to end smart manufacturing solution, integrated across functions of the business. The team applies industry-leading methodologies in automation, AI, and machine learning to enhance Micron’s product development, business, and administrative processes across the company. This role focuses on enabling semiconductor fab digital twin solutions, involves leveraging advanced analytics, machine learning, and simulation technologies to model fab operations, predict performance, and enable real-time decision-making.

Responsibilities

• Work with an international team of data scientists, data engineers, solution architect, external solution provider, and our stakeholders in construction, facility, planning teams in a collaborative manner to create highly accurate digital twins of our fabs and enable more advanced capabilities, e.g., Photorealistic and physics-based simulation, etc.
• Digital Twin Development
• Build and maintain data-driven models representing fab processes, equipment behavior, and subfab utilities.
• Integrate IoT sensor data, MES (Manufacturing Execution System) data, and facility data into the digital twin platform.
• Predictive Analytics & Machine Learning
• Develop algorithms for predictive maintenance, throughput optimization, and energy efficiency.
• Apply statistical and ML techniques to forecast equipment failures, cycle time variations, and yield impacts.
• Simulation & Optimization
• Use simulation tools (e.g., NVIDIA Omniverse) to run what-if scenarios for layout changes, capacity planning, and process improvements.
• Optimize fab workflows for cost, energy, and productivity.
• Data Integration & Visualization
• Design dashboards for real-time monitoring of fab KPIs (e.g., OEE, WIP, energy consumption).
• Collaborate with engineering teams to visualize fab layouts and operational states in 3D environments.
• Collaboration
• Work closely with process engineers, facility planners, and IT teams to ensure seamless integration of digital twin solutions.
• Support cross-functional projects involving AI, automation, and Industry 4.0 initiatives.

Required Skills

• Strong proficiency in Python, R, SQL, and data engineering.
• Experience with machine learning frameworks (TensorFlow, PyTorch) and simulation tools.
• Knowledge of semiconductor manufacturing processes and fab operations.
• Familiarity with IoT data pipelines, MES systems, and cloud platforms (AWS, Azure).
• Understanding of 3D modeling and visualization tools (Omniverse, Unity, or similar).