Job Description

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

Responsibilities:

  • Lead the end to end design, development, and deployment of machine learning models and analytical solutions for global manufacturing and engineering operations.

  • Collaborate with Smart Manufacturing Strategy Leads to align data science efforts with business goals across Micron sites. 

  • Provide mentorship and coaching to data scientists and engineers to nurture their technical skills. 

  • Provide technical consulting and hands-on assistance to site teams to identify, evaluate, and implement optimal solutions. 

  • Conduct interviews and prototype development to validate use cases and demonstrate successful applications. 

  • Perform exploratory data analysis and feature engineering on structured and unstructured data. 

    • Technical Skills & Expertise

    Must-Have:

  • Fluency in Python for data analysis and modeling. 

  • Strong understanding of statistical modeling, supervised/unsupervised/semi-supervised learning. 

  • Experience with SQL and data extraction from relational databases. 

  • Proficiency in cloud-based analytics platforms and distributed computing (, PySpark, Hadoop). 

  • Experience with TensorFlow, Keras, or similar frameworks. 

  • Strong software development skills with OOP principles. 

  • Experience with time-series data, image data, and anomaly detection. 

  • Familiarity with Manufacturing Execution Systems (MES). 

  • Familiarity with full-stack development and UI/UX building, including AngularJS experience. 

    • Nice-to-Have:

  • Experience with JavaScript, AngularJS , Tableau for dashboarding and visualization. 

  • Exposure to SSIS, ETL tools, and API development. 

  • Knowledge of statistical software and scripting for automated analyses. 

  • Familiarity with publishing or reviewing papers in CVPR, NIPS, ICML, KDD.

  • Cloud knowledge (GCP or similar) is an added advantage. 

    • Leadership & Communication

  • Proven ability to lead and manage data science projects and teams. 

  • Ability to work in a dynamic, fast-paced environment with minimal supervision. 

  • Proficiency in communicating effectively with globally distributed teams and interested parties.

  • Strong interpersonal skills with the ability to influence and present to diverse audiences. 

    • Education Requirements

  • Bachelor’s or Master’s degree in Computer Science, Electrical/Electronic Engineering, Data Science, or a related field, or equivalent experience.

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