Senior Manager, Data Science, SMAI
Fab 10A, Singapore
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead and grow global engineering and analytics teams, including hiring and mentoring
Analyze inline, parametric and probe data to find yield detractors and fix manufacturing issues
Build data pipelines and automated solutions from SQL, sensor and fab equipment data
Design and analyze experiments (DOE) with process engineers to improve process capability
Build dashboards and tools with Dash, Plotly and Streamlit for engineering stakeholders
From the employer’s posting
Lead and develop global engineering and analytics teams across multiple levels. Recruit, mentor, and grow analysts, engineers, and contractors
identify key yield detractors, troubleshoot manufacturing issues, and drive continuous improvement
Extract, cleanse, integrate, and analyze large datasets from SQL databases, sensor networks, fabrication equipment
Partner with Process and Integration Engineers to design and analyze Design of Experiments (DOE)
Develop automated reports, analytical tools, prototypes, and dashboards using technologies such as Dash, Plotly, and Streamlit
What you’ll bring
All qualificationsCore experience
- Master’s degree in Computer Science, Electronics Engineering, or a related technical discipline.
- Demonstrated ability to translate complex semiconductor manufacturing data into practical engineering insights and solutions.
- 8+ years of experience with data visualization and application development technologies such as Dash, Plotly, and Angular.
- 12+ years of overall professional experience, including at least 2–3 years leading global Analytics and/or Data Science teams.
- Experience with engineering and delivery tools such as GitHub and JIRA.
- Solid understanding of semiconductor fabrication processes, manufacturing equipment, and device physics.
Qualification wording
Master’s degree in Computer Science, Electronics Engineering, or a related technical discipline.
Demonstrated ability to translate complex semiconductor manufacturing data into practical engineering insights and solutions.
8+ years of experience with data visualization and application development technologies such as Dash, Plotly, and Angular.
12+ years of overall professional experience, including at least 2–3 years leading global Analytics and/or Data Science teams.
Experience with engineering and delivery tools such as GitHub and JIRA.
Solid understanding of semiconductor fabrication processes, manufacturing equipment, and device physics.
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.
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.
- 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.
- 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.
- 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.
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.
Posting record
Report an errorActively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 20, 2026 · 9 days ago
- Recorded sightings
- 33
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on micron.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
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.
We are looking for an accomplished Manager, Data Science to lead the next evolution of our TD NAND data science and analytics capabilities in Singapore.
This is a high-impact leadership role at the intersection of semiconductor manufacturing, data science, advanced analytics, and engineering. You will lead teams that apply statistical methods, machine learning, data engineering, and advanced analytics to solve complex manufacturing challenges and improve process capability, device yield, and operational performance.
Working closely with Process Integration, Process Engineering, Inline/Metrology/RDA, Yield, and other cross-functional engineering teams, you will transform large and complex datasets into actionable engineering insights.
You will also play a hands-on role in shaping analytical approaches, developing prototypes, enabling rapid ad-hoc analysis, identifying sources of variation (SOV), and building scalable algorithms and automated data solutions using inline, parametric, probe, sensor, and equipment data.
Because of the highly technical nature of this role, strong semiconductor manufacturing knowledge and experience are essential.
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
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
- 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
- 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.
About Micron Technology, Inc.
We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® and Crucial® brands. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience.
To learn more, please visit micron.com/careers
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.
To request assistance with the application process and/or for reasonable accommodations, please contact hrsupport_sg@micron.com
Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.
Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.
AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.
Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Fab 10A, Singapore
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.