One Thing
Semiconductor
SMAIDataScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“SMAI Data Scientist at One Thing. Skills: Data Science, Machine Learning, Data Engineering. Design, develop, and program methods, processes, and systems. Generate actionable insights and solutions for client services”
What You'll Achieve.
Continuously improve production metrics
Industry & Context.
Problem solving; Structured approaches; Logic approaches
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Data Science, Industrial Engineering, Operations Research or equivalent, Demonstrated programming and modeling capabilities, Past experience in semiconductor industry, Past experience in simulation modeling, Past experience in optimization modeling, Knowledge and past experience with cloud solutions, Knowledge and past experience with API, Knowledge and past experience with GIT, Knowledge and past experience with ETL, Past experience in JAVA, Past experience in Python, Past experience in SQL, Past experience in HTML, Past experience in C/C++, Past experience in CSS, Demonstrated fast learning capacities in programing languages, Problem solving skills with structured & logic approaches, Clear & effective communication skills
Nice to Have
Past experience in semiconductor operations digital twin, Past experience in optimization modeling or Operations Research using mix integer programming, linear programming, etc.
What You'll Do.
Generate actionable insights and solutions for client services
Interact with product and service teams to identify
Develop and code software programs
Identify meaningful insights from large data and metadata
Interpret and communicate insights and findings from analysis
Explore and apply new frontier ideas
Enable breakthrough solutions at Micron
different departments
and global manufacturing
Deliver solutions to continuously improve production metrics
Drive global collaboration
and benchmarking of optimization
How You'll Work.
Team & Collaboration
Data Scientists; Data Engineers; Business Areas Engineers; UX teams; Product and service teams; Management; Different departments; Global manufacturing sites
Communication Scope
Clear communication; Effective communication
Full Job Description
**Our vision is to transform how the world uses information to enrich life for all.** Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. As a Data Science Engineer at Micron, you will employ techniques and theories drawn from areas of mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data from which predictive models, actionable insights, and solutions can be developed. You will interact with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify questions and issues for data analysis projects and improvement of existing tools. In this position, you will help develop software programs, algorithms and/or automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. There will be significant opportunities to perform exploratory and new solution development activities. **Responsibilities include, but not limited to:** * Design, develop, and program methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. * Interact with product and service teams to identify questions and issues for data analysis and experiments. * Develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. * Identify meaningful insights from large data and metadata sources. * Interpret and communicate insights and findings from analysis and experiments to product,
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