Manager, Data Science, SMAI

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE. LTD. seeks a senior leader to drive analytics across global teams in a semiconductor setting. You will mentor engineers and analysts, oversee multi-stream delivery, and champion data-driven decision making to improve yield and process performance.

You will leverage Python, SQL, GCP, and Snowflake to build scalable data pipelines, perform advanced modeling, and deliver dashboards that communicate complex insights to engineering stakeholders.

Qualifications

• Minimum 12+ years overall experience with at least 2-3 years leading global Analytics and/or Data Science teams.
• Experience in the semiconductor industry and understanding of fabrication processes, equipment, and device physics is essential.
• Knowledge of memory architecture (NAND) is a plus.

Responsibilities

• Lead and develop global engineering and analytics teams across multiple levels; recruit, mentor, and grow analysts and engineers.
• Drive yield and process optimization by collaborating with manufacturing teams to identify top detractors and implement improvements.
• Build and maintain data pipelines extracting from SQL databases and tool logs to support operations.
• Apply advanced analytics and machine learning to troubleshoot yield issues and support defect reduction.
• Support Design of Experiments (DOE) and analyze results to enhance process capabilities.
• Create automated reports and dashboards using Dash, Plotly, and similar tools for stakeholder communication.
• Manage multi-stream delivery with transparent priorities and alignment across Yield, LPD, Cost, IET, and Planning.

Skills

Python

SQL

GCP

Snowflake

Dash

Plotly

Angular

Github

JIRA

Github Copilot

Tools

Github

JIRA

Dash

Plotly

Angular

Open Code

Roo Code

Job description

What You'll Do

• Team Leadership & Talent Development: Lead and develop global engineering and analytics teams across multiple levels. Recruit, mentor, and grow analysts, engineers, and contractors into high-performing contributors. Foster a culture of technical excellence, collaboration, and continuous improvement.
• 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 troubleshoot 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 (e.g., Dash, Plotly, streamlit) to communicate technical concepts and project outcomes effectively to engineering stakeholders.
• Cross-Functional Execution & Governance: Manage a multi-stream delivery portfolio with predictable, high-quality releases. Partner with Yield, LPD, Cost, IET, Planning leaders to maintain prioritization, risk transparency, and dependency alignment.

What You Bring

Experience & Leadership

Prior experience in the semiconductor industry is must. Understanding of semiconductor fabrication processes, equipment, and device physics is must.

Minimum 12+ years overall experience with at least 2-3 years experience in leading global Analytics and/or Data Science teams.

Proven success delivering multi-stream, cross-functional data engineering programs.

Experience with AI-driven engineering acceleration and modern data-stack standardization.

Strong track record improving data quality, release predictability, and platform performance.

Ability to mentor technical talent and influence architectural direction.

Excellent stakeholder engagement and cross-functional communication skills.

Knowledge of memory architecture (NAND) is added advantage.

Technical Skills

• Programming & Data Engineering: Minimum 8 years of experience in Python programming skills and experience with SQL for data extraction and manipulation. Cloud & Data Platforms: GCP Suite, Snowflake,
• Statistical Analysis: Minimum 8 years of expertise in role which is with statistical tools, methodologies (such as SPC, DOE, or FDC/EDA), and data-driven problem solving.
• Data Visualization: At least 8 years of working experience utilizing data visualization tools (e.g., Dash, Plotly, Angular) to present complex engineering data clearly.
• Engineering & Delivery: Experience in Github, JIRA will be plus.
• Expertise in Code Gen tools: Code Assist, Open Code, Roo Code, Github copilot will be important.