One Thing
DATASCIENTIST
Neural analysis suggests this role is
optimal for Mid+ candidates.
“DATA SCIENTIST at One Thing. Skills: Data Science, Machine Learning, Data Analysis, AI. Design, develop, and program methods, processes, and systems. Generate actionable insights and solutions for client services”
Industry & Context.
Problem-solving skills; Root cause analysis
What They're Looking For.
Must Have
Degree in Computer Science, Mathematics, Statistics, Data Science or related fields, Foundation in statistical modeling, advanced analytics, and modern machine learning techniques, Extract data from databases via SQL and other query languages, Apply data cleansing, outlier identification, and missing data techniques, Proficiency with data visualization tools (Tableau, PowerBI etc), Proficiency building interactive UIs using frameworks (Streamlit, React, Angular, or similar), Proficiency in Python and other programming skills, Excellent communication and presentation skills, Excellent problem-solving skills, Able to work independently and collaborate effectively with diverse teams, Proven ability to work independently, manage multiple priorities, and deliver high-quality results, Integrates AI-assisted tools and insights into daily work, Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements
Nice to Have
Experience with cloud platforms (GCP, AWS etc), Cloud certifications, Exposure to semiconductor industry, Experience in web development, Experience with generative AI and large language models (LLMs), RAG, LLM tuning, and development of agents, Contributions to top-tier conferences (CVPR, NeurIPS, ICML, or KDD), Apply baseline digital fluency and role-appropriate AI literacy to use AI-enabled tools responsibly and effectively
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
Deploy data science models
Own the end-to-end life cycle
including solution design
Identify relevant insights from large data and metadata
Interpret and communicate insights and findings from analysis
How You'll Work.
Team & Collaboration
Diverse teams; Product teams; Service teams; Business Areas Engineers; UX teams
Communication Scope
Presentation skills; Convey complex data insights to non-technical audiences
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 Scientist 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. ## ## Primary Responsibility, 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 improvement. * 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. * Deploy data science models and own the end-to-end life cycle, including solution design, development, deployment, model maintenance and monitoring. * Identify relevant
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