Position:
- Data Scientist
Company:
- Micron Technology, Inc.
Location:
- Boise, Idaho, United States of America
Job Type:
- Full-Time
Job Mode:
- Hybrid (As per company policies and project requirements)
Job Requisition ID:
- Not Provided / 27796324
Years of Experience:
- Not Mentioned; as per JD looks like an entry level role; 0-3 years
Company Description:
- Micron Technology, Inc. is a globally recognized leader in the semiconductor industry, specializing in the production of memory and storage solutions. The company is renowned for its innovative approach to transforming data into actionable insights, enabling technological advancements across various sectors. Micron’s mission is to accelerate the adoption of cutting-edge technologies by delivering high-performance products that enhance computing experiences and address the evolving needs of the digital world.
- Headquartered in Boise, Idaho, Micron operates in multiple regions worldwide, ensuring that its customers receive the highest quality solutions. The company’s extensive portfolio includes DRAM, NAND, and NOR memory products, catering to industries such as artificial intelligence, cloud computing, automotive, and mobile. Micron’s commitment to sustainability, diversity, and technological excellence has positioned it as a trusted partner for enterprises seeking to optimize their data-centric operations.
- With a focus on continuous innovation and a collaborative culture, Micron empowers its employees to explore new ideas and drive technological breakthroughs. The company invests heavily in research and development, ensuring that its products remain at the forefront of the semiconductor industry. Micron’s dedication to corporate social responsibility and environmental sustainability reinforces its reputation as a responsible and forward-thinking organization.
Profile Overview:
- The Data Scientist role at Micron involves applying advanced techniques and methodologies derived from disciplines such as mathematics, statistics, semiconductor physics, materials science, and information technology. The primary objective is to uncover patterns in extensive datasets to develop predictive models, derive actionable insights, and create scalable solutions.
- As a Data Science Engineer, you will work closely with cross-functional teams, including expert Data Scientists, Data Engineers, Business Area Engineers, and UI/UX teams. This collaboration aims to identify complex data-related challenges, develop solutions, and enhance existing analytical tools and models. The role requires a deep understanding of data engineering, machine learning, and data analysis techniques.
- The ideal candidate will possess exceptional programming skills, experience with SQL and other query languages, and the ability to develop and deploy machine learning models. The role also involves creating and refining algorithms to process and analyze vast amounts of structured and unstructured data in an automated industrial manufacturing environment. Strong communication skills are essential to effectively articulate complex AI concepts to business stakeholders and influence decision-making processes.
Responsibilities:
Collaborate with Cross-Functional Teams:
- Partner with expert Data Scientists, Data Engineers, Business Area Engineers, and UI/UX teams to identify key questions and challenges related to data analysis.
- Participate in brainstorming sessions to define project goals and develop innovative solutions to enhance existing tools and processes.
- Work with business and engineering teams to understand data requirements, ensuring alignment with strategic objectives.
Develop and Enhance Software Programs:
- Design and implement software programs, algorithms, and automated processes to cleanse, integrate, and analyze large datasets from multiple sources.
- Optimize and automate data pipelines to ensure seamless data processing and transformation.
- Develop scalable solutions to handle terabytes and petabytes of structured and unstructured data in industrial manufacturing environments.
Perform Machine Learning and Data Analysis:
- Apply statistical modeling techniques and feature extraction methods in supervised, unsupervised, and semi-supervised learning environments.
- Analyze large-scale datasets using advanced machine learning models to uncover actionable insights.
- Identify data anomalies, apply data cleansing techniques, and ensure data integrity for accurate analysis.
Extract and Clean Data:
- Retrieve data from various databases using SQL and other query languages.
- Apply data preprocessing techniques, including outlier identification and handling missing values, to ensure data quality.
- Develop and maintain data pipelines that integrate data from diverse sources for analytical purposes.
Qualifications:
Minimum Qualifications:
-
Ability to Translate AI Concepts:
- Strong communication skills to articulate complex AI and machine learning concepts in business terms.
- Ability to present data analysis and insights effectively to key stakeholders.
-
Proficiency in Programming and Databases:
- Expertise in Python for data analysis, modeling, and automation.
- Strong knowledge of relational database technologies such as Snowflake, MySQL, and other relevant platforms.
- Experience using lightweight user interface frameworks such as Streamlit and visualization tools like Tableau.
-
Image Analysis, Neural Networks, and NLP:
- Hands-on experience in image analysis, neural networks, and natural language processing (NLP).
- Ability to implement models and algorithms for computer vision and language-based applications.
-
Strong Software Development Skills:
- Ability to design, develop, and deploy robust software solutions.
- Experience in developing scalable and maintainable codebases.
Preferred Qualifications:
-
Generative AI and Advanced Techniques:
- Exposure to Generative AI (GenAI), including concepts such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents.
- Hands-on experience with the latest AI techniques and frameworks.
-
Proficiency in JavaScript and Front-End Technologies:
- Knowledge of JavaScript and frameworks such as AngularJS 2.0.
- Experience in developing and maintaining web applications for data visualization and interaction.
-
Time-Series Data Expertise:
- Familiarity with time-series data analysis and modeling techniques.
- Ability to extract insights from time-dependent datasets.
-
Exposure to Semiconductor Industry:
- Prior experience or exposure to semiconductor manufacturing processes and industry standards.
- Understanding of domain-specific challenges and requirements.
-
Published Research or Conference Papers:
- Contribution to key conferences such as CVPR, NIPS, ICML, and KDD is a plus, although this role is not primarily research-focused.
Additional Info:
Key Skills Required:
-
Data Science and Analytics:
- Expertise in machine learning, statistical modeling, and data analysis.
- Ability to build, test, and deploy predictive models in industrial environments.
-
Programming and Software Development:
- Proficiency in Python, SQL, and other relevant programming languages.
- Experience in developing APIs, automation scripts, and scalable data pipelines.
-
Data Visualization and UI Development:
- Proficiency in data visualization tools such as Tableau and Streamlit.
- Strong understanding of user interface development and data presentation.
-
Problem-Solving and Critical Thinking:
- Analytical mindset with a strong ability to solve complex data-related challenges.
- Ability to think strategically and develop innovative solutions.
Ideal Candidate Profile:
-
Educational Background:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
- Strong foundation in AI, machine learning, and data analytics.
-
Professional Experience:
- Prior experience working in data-intensive environments, preferably in the semiconductor or related industries.
- Experience collaborating with cross-functional teams to deliver data-driven solutions.
-
Soft Skills and Communication:
- Strong interpersonal and communication skills to engage with technical and non-technical stakeholders.
- Ability to work in a fast-paced environment while managing multiple priorities effectively.
Work Environment:
-
Collaborative and Innovative Culture:
- Opportunity to work with a diverse team of experts in a dynamic and challenging environment.
- Exposure to cutting-edge technologies and the latest advancements in AI and machine learning.
-
Career Growth and Development:
- Access to ongoing learning opportunities, mentorship, and professional development programs.
- Potential for career advancement in a rapidly evolving industry.
Additional Considerations:
-
Flexible Work Arrangements:
- The role may offer flexible work arrangements based on project requirements and team collaboration needs.
- Hybrid work options may be available depending on organizational policies.
-
Commitment to Diversity and Inclusion:
- Micron is committed to fostering an inclusive and diverse work environment.
- Equal opportunity employer that values diverse perspectives and contributions.
Please click here to apply.
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