Manager, Data Science, Semiconductor Yield (SMAI)

About the role

Micron is looking for a Manager, Data Science within its Semiconductor Manufacturing Analytics (SMAI) team. The role leads global engineering and analytics teams and applies data science to semiconductor manufacturing, focusing on yield improvement, defect reduction and data pipeline automation.

Key responsibilities

• Lead and develop global engineering and analytics teams, recruiting, mentoring and growing analysts, engineers and contractors.
• Work with semiconductor manufacturing engineering teams to analyse inline, parametric and probe data and identify yield detractors.
• Extract, cleanse and analyse datasets from SQL databases, sensor networks and fabrication tool logs.
• Apply data science, statistical modelling and machine learning to troubleshoot yield issues and support defect reduction.
• Support process and integration engineers with Design of Experiments (DOE).
• Build automated reports and dashboards (e.g. Dash, Plotly, Streamlit) for engineering stakeholders.
• Manage a multi-stream delivery portfolio with predictable releases, partnering with Yield, LPD, Cost, IET and Planning leaders.

Required profile

• Masters degree in Computer Science or Electronics Engineering.
• Prior experience in the semiconductor industry is mandatory, including understanding of fabrication processes, equipment and device physics.
• At least 12 years of overall experience, with at least 2-3 years leading global analytics and/or data science teams.

Required skills

• Python programming and SQL for data extraction and manipulation (minimum 8 years).
• GCP suite and Snowflake.
• Statistical analysis with tools such as SPC, DOE and FDC/EDA (minimum 8 years).
• Data visualization tools such as Dash, Plotly and Streamlit (highly desirable, 8+ years).
• GitHub and JIRA experience is a plus; code generation tools such as GitHub Copilot are important.