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DATA SCIENTIST

Micron Technology

DATA SCIENTIST

full-timePosted: Sep 1, 2026Singapore, Fab 10A

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.Key ResponsibilitiesYield & 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 solve 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, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders.Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomesRequired QualificationsBachelor's degree in Computer Science, Data Science, Statistics, AI, or a related Engineering field.At-least-half-a-year working-level hands-on experience in data science, analytics, or scripting applications.Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers to resolve production issues.Required Technical ExperienceProgramming & Data Engineering: Strong Python programming skills and at-least-half-a-year working experience with SQL for data extraction and manipulation.Statistical Analysis: Familiarity with statistical tools, methodologies (such as SPC, DOE, or FDC/EDA), and data-driven problem solving.Data Visualization: at-least-half-a-year experience applying data visualization tools (e.g., Dash, Plotly, Angular) to present complex engineering data clearly.Preferred ExperiencePrior experience or internship in the semiconductor industry, electronics manufacturing, or related fields.Basic understanding of semiconductor fabrication processes, equipment, and device physics (e.g., CMOS basic knowledge).Familiarity with advanced analytics or computer-based analysis for manufacturing and yield applications.Knowledge of memory architecture (DRAM/NAND).Required Soft SkillsEffective communicator and collaborator, capable of bridging the gap between data science and traditional semiconductor engineering teams.Analytical and problem-solving mentality with a demonstrated commitment to quality and continuous improvement in a fast-paced environment.Proven ability to work independently, manage multiple priorities, and deliver high-quality results.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/careersAll 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.comMicron 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.

Locations

  • Singapore, Fab 10A

Skills Required

  • data scienceintermediate
  • SQL for data extractionintermediate
  • statistical toolsintermediate
  • advanced analyticsintermediate
  • memory architectureintermediate

Required Qualifications

  • Bachelor's degree in Computer Science, Data Science, Statistics, AI, or a related Engineering field. (degree in computer science)
  • At-least-half-a-year working-level hands-on experience in data science, analytics, or scripting applications. (experience)
  • Willingness to learn semiconductor manufacturing principles and collaborate closely with equipment and integration engineers to resolve production issues. (experience)
  • Programming & Data Engineering: Strong Python programming skills and at-least-half-a-year working experience with SQL for data extraction and manipulation. (experience)
  • Statistical Analysis: Familiarity with statistical tools, methodologies (such as SPC, DOE, or FDC/EDA), and data-driven problem solving. (experience)
  • Data Visualization: at-least-half-a-year experience applying data visualization tools (e.g., Dash, Plotly, Angular) to present complex engineering data clearly. (experience)
  • Effective communicator and collaborator, capable of bridging the gap between data science and traditional semiconductor engineering teams. (experience)
  • Analytical and problem-solving mentality with a demonstrated commitment to quality and continuous improvement in a fast-paced environment. (experience)
  • Proven ability to work independently, manage multiple priorities, and deliver high-quality results. (experience)

Preferred Qualifications

  • Prior experience or internship in the semiconductor industry, electronics manufacturing, or related fields. (experience)
  • Basic understanding of semiconductor fabrication processes, equipment, and device physics (e.g., CMOS basic knowledge). (experience)
  • Familiarity with advanced analytics or computer-based analysis for manufacturing and yield applications. (experience)
  • Knowledge of memory architecture (DRAM/NAND). (experience)

Responsibilities

  • 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 solve 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, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders.
  • Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
  • Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
  • Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes

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