Job description
Join Micron Semiconductors as a Data Scientist for SMAI (Smart Manufacturing Analytics & Insights) in Singapore. This role offers diverse opportunities to apply big data analytics, machine learning, and data visualization to optimize semiconductor manufacturing processes. You will collaborate with world-class engineers and operations teams to turn data into actionable insights that drive yield, quality, and efficiency.
At Micron, you will leverage large-scale sensor data, MES, and other manufacturing systems to build models that forecast equipment failures, optimize process parameters, and improve product quality. You will own end-to-end data science projects from data wrangling to model deployment, and communicate results in clear, business-relevant terms. We value curiosity, collaboration, and a pragmatic approach to turning data into impact.
What you’ll do is empower manufacturing with data-driven decisions: designing experiments, deploying scalable models, and delivering dashboards that support real-time decision making. If you are excited to push the boundaries of analytics in the semiconductor space, this is the role for you.
Why Micron? You’ll join a global leader in memory and storage solutions, work alongside engineers who shape product quality, and contribute to innovations that enable smarter, faster, and more reliable electronics worldwide.
Responsibility
- Build, validate, and deploy predictive models to reduce downtime, optimize yields, and improve product quality in semiconductor manufacturing.
- Ingest, clean, and wrangle large-scale data from sensors, MES, ERP, and other manufacturing systems.
- Develop ML algorithms for anomaly detection, predictive maintenance, process optimization, and yield improvement.
- Create interactive dashboards and reports for engineering and operations using visualization tools and Python-based dashboards.
- Collaborate with data engineers, software engineers, device and process engineers to translate business needs into data-driven solutions.
- Design and run experiments, A/B tests, and statistically analyze results to drive decisions.
- Monitor model performance, implement data governance, version control, and ensure robust production operation.
- Communicate insights clearly to non-technical stakeholders and help shape manufacturing strategy.
Qualification
- Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Engineering or a related field.
- Strong proficiency in Python and SQL; experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and data visualization tools.
- Experience with big data technologies (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
- Familiarity with manufacturing data, process control, statistics, and experimental design.
- Knowledge of semiconductor manufacturing domain is a plus.
- Excellent problem-solving, communication, and stakeholder management skills.
- Ability to deploy models to production and monitor performance; familiarity with version control and CI/CD basics.
- Strong data storytelling skills and the ability to translate complex results into actionable business decisions.