Summer 2027 Data Scientist Intern -Bachelor's (Austin, TX)
About The Position
Applied Materials is hiring a Summer 2027 Data Scientist Intern for its Supply Chain Analytics team in Austin, Texas. The team uses machine learning, statistical and simulation modeling, generative AI, visualization, and actionable insights to improve process efficiency, decision support, and business metrics. The intern will learn how supply chain operations work and how their data informs decisions, then help develop analytical solutions that support supply chain decision-making. The role combines technical work with collaboration. The intern will analyze data, build statistical and machine learning models, contribute to GenAI and LLM applications, and design dashboards and reports. They will work with stakeholders to understand business challenges, translate requirements into scalable solutions, and communicate findings to technical and non-technical audiences. The team values strong fundamentals, careful examination of data and model assumptions, and responsible use of AI tools. Applicants must be currently pursuing a bachelor's degree in a quantitative field such as Data Science, Computer Science, Engineering, Statistics, Operations Research, or Supply Chain Analytics. A GPA of 3.0 or above is preferred. Prior supply chain experience is preferred but not required. Applications are reviewed on a rolling basis; applicants are asked to apply by November 30, 2026, and the position may close earlier depending on application volume or candidate selection.
Requirements
- Currently pursuing a bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, Supply Chain Analytics, or another quantitative field.
- Coursework or hands-on experience with databases and data modeling, including RDBMS concepts, primary and foreign keys, table relationships, and basic normalization.
- Working knowledge of SQL, including joins, aggregations, and subqueries.
- Working knowledge of Python for data analysis, including Pandas and NumPy.
- Introductory statistics and machine learning fundamentals, including supervised versus unsupervised methods, train/test splits, basic evaluation metrics, distributions, and correlation versus causation.
- Familiarity with data visualization using Tableau, Power BI, or a comparable tool.
- Ability to learn a new domain quickly, ask questions, and use feedback to improve work.
- Ability to investigate data, trace figures from their source through the relevant tables to decisions, collaborate with stakeholders, and take initiative.
Nice To Haves
- GPA of 3.0 or above.
- Knowledge of SQL CTEs and window functions.
- Exposure to data engineering concepts such as ETL/ELT, ingestion from multiple sources, and pipeline design.
- Exposure to GenAI and LLMs, including prompting, retrieval-augmented generation, LLM APIs, and output evaluation.
- Familiarity with version control frameworks such as Git and Bitbucket.
- Coursework or project experience with cloud data platforms and data at scale, such as Databricks, Snowflake, or BigQuery, including distributed processing and partitioning concepts.
- Prior supply chain experience.
- Interest in supply chain or a stated desire to build a career in supply chain and operations.
- A supply chain project completed end to end, from raw data to something used by others.
- Class or personal projects using LLM applications such as RAG pipelines, agents, or evaluation harnesses.
- A public portfolio, such as GitHub, Kaggle, or Tableau Public, demonstrating applied projects.
Responsibilities
- Learn supply chain operations, the meaning of underlying data, and where decisions are made.
- Perform exploratory data analysis to identify trends, opportunities, and actionable insights.
- Write and optimize SQL queries to extract, transform, and analyze data from multiple sources.
- Develop statistical and machine learning models to support supply chain decision-making.
- Contribute to GenAI and LLM initiatives, including AI-powered search, automation, and business applications, and build reusable components where applicable.
- Design and enhance dashboards and reports using Tableau, Power BI, or custom-built tools.
- Partner with stakeholders to understand business challenges, gather requirements, and identify opportunities for improvement.
- Translate business needs into technical requirements and develop scalable analytical solutions.
- Communicate findings and recommendations to technical and non-technical audiences.
Benefits
- Comprehensive benefits package.
- Candidates may be eligible for participation in a bonus program and a stock award program, as applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
