STAFF DATA SCIENTIST

Micron Technology; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

Micron Technology in Singapore is seeking a Data Scientist to collaborate with engineering teams to enhance semiconductor manufacturing processes. The ideal candidate will have a Bachelor's degree in a relevant field and at least 5 years of experience in data science. Key responsibilities include analyzing yield data, applying data science techniques, and developing automated dashboards. This role requires strong programming skills in Python and SQL, and experience with data visualization tools like Dash and Plotly. Micron offers a dynamic work environment committed to innovation.

Qualifications

• Minimum 5 years of hands-on experience in data science, analytics, or scripting applications.
• Willingness to learn semiconductor manufacturing principles.

Responsibilities

• Collaborate with teams to analyze inline/param/probe data.
• Extract, cleanse, and analyze datasets from SQL databases.
• Apply data science techniques to solve yield issues.
• Assist process engineers in running and analyzing DOEs.
• Develop automated reports and dashboards using visualization tools.

Skills

Data Science

Statistical Analysis

Data Visualization

Problem Solving

Collaboration

Education

Bachelor's degree in Computer Science, Data Science, Statistics, AI, or related Engineering field

Tools

Python

SQL

Dash

Plotly

Angular

Job description

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.

Key Responsibilities

• Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement.
• Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operations.
• Advanced Analytics & Modeling: Apply data science techniques, statistical modeling, and machine learning to solve yield issues and support defect reduction strategies.
• Experimentation Support: Assist process and integration engineers in running and analyzing Design of Experiments (DOE) to enhance process capabilities and margins.
• Visualization & Communication: Develop automated reports and dashboards using visualization tools (Dash, Plotly, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, AI, or a related Engineering field.
• Minimum 5 years of hands‑on experience in data science, analytics, or scripting applications.
• Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers to resolve production issues.

Required Technical Experience

• Programming & Data Engineering: Strong Python programming skills and working experience with SQL for data extraction and manipulation.
• Statistical Analysis: Familiarity with statistical tools, methodologies (such as SPC, DOE, or FDC/EDA), and data‑driven problem solving.
• Data Visualization: At least 3 years of working experience applying data visualization tools (Dash, Plotly, Angular) to present complex engineering data clearly.

Preferred Experience

• Prior experience or internship in the semiconductor industry, electronics manufacturing, or related fields.
• Basic understanding of semiconductor fabrication processes, equipment, and device physics (e.g., CMOS basic knowledge).
• Familiarity with advanced analytics or computer‑based analysis for manufacturing and yield applications.
• Knowledge of memory architecture (DRAM/NAND).

Required Soft Skills

• Effective communicator and collaborator, capable of bridging the gap between data science and traditional semiconductor engineering teams.
• Analytical and problem‑solving mentality with a demonstrated commitment to quality and continuous improvement in a fast‑paced environment.
• Proven ability to work independently, manage multiple priorities, and deliver high‑quality results.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.