Sr Data Scientist

1000 Micron Technology, Inc.; Boise (ID); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Medical, dental, and vision plans

Paid family leave

Robust paid time-off program

Paid holidays

Job summary

1000 Micron Technology, Inc. is seeking a Data Science Engineer in Boise, ID, to innovate memory and storage solutions. You will analyze semiconductor data, develop predictive models, and collaborate with engineering teams.

The ideal candidate has a B.S./M.S. in a relevant field, strong Python skills, and 3+ years of experience in data science with a focus on statistical modeling and machine learning. Micron offers robust benefits and fosters a diverse working environment.

Qualifications

• 3+ years of experience in data science within engineering or a related industry.
• In-depth knowledge of statistical modeling, machine learning, and deep learning.
• Strong Python skills and familiarity with machine-learning frameworks.

Responsibilities

• Perform exploratory data analysis on semiconductor manufacturing data.
• Develop predictive models to optimize manufacturing processes.
• Build clear and informative visualizations to communicate findings.
• Collaborate with engineers to translate business requirements.
• Stay up to date with industry trends and research in data science.

Skills

Statistical modeling

Machine learning

Deep learning

Python

SQL

Data cleansing

Effective communication

Proactive problem-solving

Collaboration

Education

B.S./M.S. in Data Science, Computer Science, Industrial Engineering

Tools

PyTorch

scikit-learn

Google Cloud Platform

Job description

Overview

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 Science Engineer at Micron, you will employ techniques and theories drawn from mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data. This role involves interacting with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify questions and issues for data analysis projects and to improve existing tools. You will help develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources, and have opportunities to perform exploratory and new solution development activities.

Responsibilities

• Data Analysis & Anomaly Detection: Perform exploratory data analysis on semiconductor manufacturing data, including wafer fabrication, yield, and defect rates. Identify anomalies and outliers, suggesting corrective actions to improve yield.
• Model Development & Feature Engineering: Develop predictive models using machine learning techniques (regression, classification, clustering) to optimize manufacturing processes and improve product quality. Extract relevant features from raw data, considering material properties, process parameters, and environmental conditions.
• Visualization: Build clear and informative visualizations to communicate findings and insights to stakeholders.
• Collaboration: Work closely with engineers and domain experts to understand semiconductor processes and translate business requirements into data-driven solutions.
• Continuous Improvement: Stay up to date with industry trends, research progress, and new technologies in data science and semiconductor manufacturing.

Minimum Qualifications

• B.S./M.S. degree or equivalent experience in Data Science, Computer Science, Industrial Engineering or another engineering field.
• 3+ years of experience in data science within engineering or a related industry with in‑depth knowledge of statistical modeling, machine learning, and deep learning.
• Strong Python skills and familiarity with at least one machine‑learning framework (e.g., PyTorch, scikit‑learn).
• Ability to extract data from different databases via SQL and other query languages, and apply data cleansing, outlier identification, and missing‑data techniques.
• Experience quickly building prototype solutions based on business requirements and deploying data‑science solutions into production environments.
• Effective communication skills for explaining models, assumptions, and results to non‑technical partners, and ability to work independently with internal and external partners to drive ideas to resolution.
• Proactive problem‑solving approach and ownership mindset.
• Passion and interest in learning semiconductor manufacturing to resolve terabytes and petabytes of data to solve memory‑wafer related problems, and enjoyment of working in a diverse environment.

Preferred Qualifications

• Ph.D. or equivalent experience in related subject areas.
• Experience working with Google Cloud Platform or another big‑data platform.
• Experience with generative‑AI solutions, including RAG, LLM tuning, and agentic problem solving.
• Solid experience with root‑cause‑analysis algorithms and modeling in solving complex industry problems.
• Full‑stack skills to build end‑to‑end data‑science applications with scalability and robustness.
• Experience with Manufacturing Execution Systems (MES), or good knowledge of wafer process and yield analysis.
• Existing papers from CVPR, NIPS, ICML, KDD, or other key conferences (this is not a research position).

Benefits

Micron is dedicated to your personal well‑being and professional growth. Benefits include a choice of medical, dental and vision plans; programs that protect income if you are unable to work due to illness or injury; paid family leave; a robust paid time‑off program; and paid holidays. Additional information regarding the benefit programs available can be found in Micron’s benefits guide.

Equal‑Opportunity Statement

Micron is a proud equal‑opportunity employer and is an affirmative‑action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.