Data Scientist

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.

As a Data Scientist at Micron Technologies, you will play a crucial role in analyzing and extracting valuable insights from large datasets related to semiconductor manufacturing, process optimization, and quality control. You'll collaborate with multi-functional teams to develop innovative solutions that improve product performance, yield, and reliability.

RESPONSIBILITIES

• Data Analysis: Perform exploratory data analysis (EDA) on semiconductor manufacturing data, including wafer fabrication, yield, and defect rates.

• Model Development: Develop predictive models using machine learning techniques (such as regression, classification, and clustering) to optimize manufacturing processes and improve product quality.

• Feature Engineering: Extract relevant features from raw data, considering factors like material properties, process parameters, and environmental conditions.

• Anomaly Detection: Identify anomalies and outliers in semiconductor production data, suggesting corrective actions to improve yield.

• Collaboration: Work closely with engineers, physicists, and domain experts to understand semiconductor processes and translate business requirements into data-driven solutions.

• Visualization: Build clear and informative visualizations to communicate findings and insights to collaborators.

• Continuous Improvement: Stay up to date with industry trends, research advancements, and emerging technologies in data science and semiconductor manufacturing.

QUALIFICATIONS

Education:

• Master’s or Ph.D. in Data Analytics, Data Science, or related field with practical experience with Virtual Metrology, AI, process control, yield improvement, quality control, semiconductor process engineering, image analytics, or related semiconductor field focus.

EXPERIENCE

Prior experience in semiconductor manufacturing, yield optimization, or process control is highly desirable.

Technical Skills:

• Proficiency in Python,

• Strong knowledge of machine learning algorithms and statistical techniques.

• Familiarity with web application and reporting, Experience with SQL and database management

Technologies:

• ML frameworks:  Decision trees, Clustering, Regression, Neural Networks, NLP, Pytorch, Big Data, Tensorflow, Pandas, Streamlit

Tools and technologies:

• Docker, Containerization, Kubernetes, Jenkins, Ansible, Elasticsearch, SSL, Microservices, data visualization tools (e.g., Streamlit, Tableau, PowerBI, etc.).

Cloud expertise:

• Google Cloud Platform, OpenShift Container Platform

AI Skills:

AI specialization and Virtual Metrology/Modeling/Computation: 

• Python library sklearn, xgboost, pycaret, etc. with the ability to learn any new package.

• Knowledgeable with the general process of data science work like data extraction, feature extraction, feature selection and modeling.

• Familiar with the skills to deal with time series data (feature extraction, modelling, similarity measure of time series).

Image specialization:

• Familiar with deep learning network CNN and package keras.

Frontend:

• Languages: HTML, CSS, JavaScript, Typescript

• Frameworks/Libraries: Angular, HighCharts, Plotly, AG Grid, BootStrap, Ngx Bootstrap, RxJS

• Packaging: npm, Jenkins

Backend/API:

• Languages: Python,

• Preferred, but not required: Java, C#, PHP, Perl, C++

• Frameworks: Flask, FastAPI, Experience with RESTful APIs, Minor experience with WSLs

• Databases: MySQL, MSSQL, Oracle, PostgreSQL, MongoDB, Neo4j, BigQuery SQL, Snowflake SQL, basic understanding of SSL

Tools:

• Git, Bitbucket

Soft Skills:

• Analytical approach and problem-solving abilities.

• Strong communication skills to work effectively with teams from various functions.

• Adaptability and willingness to learn new technologies and methodologies.

Project Skills: <