job description
Join Micron Semiconductors as a Data Scientist in Smart Manufacturing & AI and play a pivotal role in transforming semiconductor production through cutting-edge data science and artificial intelligence. Based in the vibrant tech hubs of Bali, you'll collaborate with global teams to optimize manufacturing processes, enhance predictive maintenance, and drive innovation in one of the world's most advanced semiconductor companies.
At Micron, we empower our data scientists to leverage vast datasets from our state-of-the-art fabrication facilities. Your work will directly impact operational efficiency, product quality, and sustainability initiatives. This is a unique opportunity to merge your passion for AI with real-world manufacturing challenges in a dynamic, tropical work environment.
We offer competitive compensation, flexible work arrangements, and the chance to work on projects that push the boundaries of what's possible in semiconductor manufacturing. If you're a data-driven problem solver who thrives in collaborative environments, we want to hear from you.
Responsibility
- Develop and implement machine learning models to optimize semiconductor manufacturing processes
- Design predictive maintenance systems to reduce equipment downtime and improve yield
- Analyze complex production data to identify patterns and drive continuous improvement
- Collaborate with cross-functional teams to integrate AI solutions into manufacturing workflows
- Create data visualization dashboards for real-time monitoring of production metrics
- Research and implement advanced statistical methods for quality control
- Optimize supply chain forecasting using time-series analysis and predictive modeling
- Stay current with emerging AI technologies in smart manufacturing
Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, or related field
- 3+ years of experience in data science, preferably in manufacturing or industrial settings
- Proficiency in Python, R, and SQL for data analysis and modeling
- Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn)
- Strong understanding of statistical analysis and experimental design
- Familiarity with big data technologies (Spark, Hadoop) and cloud platforms
- Excellent problem-solving skills and business acumen
- Ability to communicate complex technical concepts to non-technical stakeholders