DATA SCIENTIST

Job Overview

As a Data Scientist at Micron, you will apply innovative techniques and theories from mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data and develop predictive models, actionable insights, and transformative solutions.

You will collaborate with Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify critical questions and data analysis projects, develop software programs, algorithms, and automate processes to cleanse, integrate, and evaluate large datasets from multiple sources.

Key Responsibilities

• Build and implement computer vision systems for object detection, image segmentation, anomaly detection, and automated inspection using RGB-D cameras and vision inspection systems for volume/density measurement and component verification.
• Develop and deploy deep learning models (CNNs, LSTM, transformer-based architectures) for image classification, time-series anomaly detection, and multimodal sentiment analysis using TensorFlow, PyTorch, and Keras.
• Apply advanced AI methods such as few-shot learning, generative AI, and multimodal fusion (text, image, time-series) to address manufacturing and environmental monitoring challenges.
• Extract, cleanse, and analyze large-scale datasets from SQL databases, AWS, GCP, and sensor networks, applying rigorous outlier detection and missing data handling methods.
• Guide cross-functional cooperation among engineering, operations, and quality departments, applying experience in project management, technical writing, and training/mentoring engineers in data science tools.
• Coordinate production deployment activities using MLOps guidelines (MLflow, Apache Airflow), including model monitoring, data drift detection, versioning, and automated testing.
• Contribute to research and innovation through published patents, peer-reviewed papers, or presentations at conferences such as IJCNN, CVPR, and NeurIPS, translating research into practical solutions.
• Communicate technical concepts and project outcomes effectively to both technical and non-technical collaborators.
• Integrate 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.
• Contribute to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one's scope of work.

Required Qualifications

Possession of a Master’s degree in Computer Science, Data Science, or AI, or relevant equivalent experience. Two or more years of direct experience building and rolling out scalable AI applications in the manufacturing, semiconductor, or electronics industries. (Alternatively, a Bachelor’s degree with a minimum of three years of comparable experience.)

Required Technical Experience

• Computer Vision: at least 2 years of experience crafting and implementing computer vision models for industrial uses, including object detection, image segmentation, and automated inspection with OpenCV, YOLO, and RGB-D cameras.
• Deep Learning & AI: minimum of 2 years working with deep learning frameworks (TensorFlow, PyTorch, Keras), encompassing CNNs, LSTM, transformer models, and generative AI.
• Multimodal Analysis: demonstrated skill in handling multimodal datasets (text, image, time-series), encompassing sentiment analysis and combining various data types.
• Programming & Data Engineering: proficiency in Python, with a minimum of 2 years in SQL, Java, C++, and cloud environments (AWS, GCP); knowledge of distributed computing systems (Spark, Hadoop).
• MLOps & Deployment: familiarity with MLflow, Apache Airflow, Docker, and Git for reliable model deployment and monitoring in live environments.
• Visualization & Communication: a minimum of 2 years working with visualization tools (Dash, Plotly, Spotfire, PowerBI) and producing technical writing for documentation and training.

Required Soft Skills

• Demonstrated analytical and problem-solving skills with a data-driven approach and research perspective for at least 2 years.
• Effective communicator and collaborator, with experience in cross-functional project management and training.
• Proven ability to work independently, prioritize tasks, and deliver high-quality results in fast-paced, dynamic environments.
• Track record of dedication to quality, continuous improvement, and adaptability in manufacturing settings.

Preferred Experience

• Experience in the semiconductor industry (e.g., Intel, STMicroelectronics) or electronics manufacturing.
• Hands-on involvement in integrating computer vision or NLP solutions into production systems.
• Experience working with large language models (LLMs), multimodal sentiment analysis, or generative AI.
• Professional experience in training or instructing on data science or AI subjects.

EEO Statement

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.

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