Senior Manager, Data Science, SMAI
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- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
Education & alternatives
### Minimum Qualifications & Experience * Master’s degree in Computer Science, Electronics Engineering, or a related technical discipline. * 12+ years of overall professional experience, including at least 2–3 years leading global Analytics and/or Data Science teams. * Strong hands-on experience within the semiconductor industry. * Solid understanding of semiconductor fabrication processes, manufacturing equipment, and device physics. ### Essential Technical Expertise
Tools in this posting
- Python
- SQL
- GCP
- Snowflake
- Plotly
- Streamlit
Source — Tool mentions in context
### Essential Technical Expertise * Programming & Data Engineering: 8+ years of experience working with Python and strong proficiency in SQL for data extraction, transformation, and analysis. * Cloud & Data Platforms: Experience with GCP and Snowflake. * Statistics & Engineering Analytics: 8+ years of experience applying statistical methodologies and data-driven problem solving, including areas such as SPC, DOE, FDC, and EDA. * Demonstrated ability to translate complex semiconductor manufacturing data into practical engineering insights and solutions. ### Highly Desirable Experience
## What You’ll Do * Lead & Develop High-Performing Teams Lead and develop global engineering and analytics teams across multiple levels. Recruit, mentor, and grow analysts, engineers, and contractors while fostering a culture of technical excellence, innovation, collaboration, and continuous improvement. * Drive Yield & Process Optimization Partner with semiconductor manufacturing and engineering teams to analyze inline, parametric, and probe data, identify key yield detractors, troubleshoot manufacturing issues, and drive continuous improvement. * Build Data Pipelines & Automation Extract, cleanse, integrate, and analyze large datasets from SQL databases, sensor networks, fabrication equipment, and other manufacturing data sources. * Advance Analytics & Machine Learning Apply statistical modeling, machine learning, and data science techniques to identify patterns, understand sources of variation, troubleshoot yield issues, and support defect reduction strategies. * Enable Engineering Experimentation Partner with Process and Integration Engineers to design and analyze Design of Experiments (DOE), improving process capability, margins, and manufacturing performance. * Turn Data into Actionable Insights Develop automated reports, analytical tools, prototypes, and dashboards using technologies such as Dash, Plotly, and Streamlit, making complex engineering insights accessible to key stakeholders. * Lead Cross-Functional Execution Manage a multi-stream analytics and data engineering portfolio while partnering with Yield, LPD, Cost, IET, Planning, and other engineering leaders to align priorities, dependencies, risks, and delivery. ## What You Bring
### Highly Desirable Experience * 8+ years of experience with data visualization and application development technologies such as Dash, Plotly, and Angular. * Experience with engineering and delivery tools such as GitHub and JIRA. * Familiarity with AI-assisted development tools such as GitHub Copilot, Code Assist, OpenCode, and Roo Code. * Proven success delivering multi-stream, cross-functional data engineering and analytics programs. * Experience using AI to accelerate engineering and software development workflows. * Experience standardizing modern data platforms and improving data quality, platform performance, and release predictability. * Strong ability to mentor technical talent and influence technical and architectural direction. * Excellent stakeholder management and cross-functional communication skills. * Knowledge of NAND memory architecture is a strong advantage. Job Profile(s):
Posting record
Report an errorActively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 20, 2026 · 10 days ago
- Recorded sightings
- 39
- Last seen by us
- Oct 30, 2026
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