Lead Data Science Manager – Semiconductors

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Micron Technology, Inc. is seeking a senior leader to drive analytics across global engineering teams in Singapore. You will guide data science initiatives, optimize yield, and build scalable data pipelines drawing from SQL databases, sensor nets, and tool logs.

Expect close collaboration with manufacturing and process teams to push for continuous improvement. The role demands deep expertise in Python, SQL, cloud platforms, and statistics, with a track record of delivering multi-disciplinary

Qualifications

• Masters in Computer Science or Electronics Engineering.
• Must have experience in the semiconductor industry.
• Understanding of semiconductor fabrication processes, equipment and device physics.
• 12+ years total experience with 2–3 years leading global Analytics/Data Science teams.
• 8+ years Python and SQL data extraction/manipulation experience.
• 8+ years with statistics and data-driven problem solving (SPC/DOE/EDA).

Responsibilities

• Lead and develop global engineering and analytics teams across multiple levels.
• Collaborate with manufacturing teams to drive yield detractors to continuous improvement.
• Build data pipelines extracting from SQL databases, sensor networks, and tool logs.
• Apply data science and ML to troubleshoot yield issues and defect reduction.
• Support DOE experiments to enhance process capabilities and margins.
• Create automated reports and dashboards using Dash/Plotly/Streamlit for stakeholders.
• Manage a multi-stream delivery portfolio with prioritization and risk transparency.

Skills

Python programming

SQL data extraction

Data engineering

Statistical analysis

Education

Master's degree in CS or Electronics Engineering

Tools

GCP Suite

Snowflake

Dash

Plotly

Angular

Github

JIRA

Job description

Micron Technology, Inc. is seeking a senior leader to drive analytics across global engineering teams in Singapore. You will guide data science initiatives, optimize yield, and build scalable data pipelines drawing from SQL databases, sensor nets, and tool logs.

Expect close collaboration with manufacturing and process teams to push for continuous improvement. The role demands deep expertise in Python, SQL, cloud platforms, and statistics, with a track record of delivering multi-disciplinary