Summer 2027 Data Scientist Intern - Master's (Santa Clara, CA)

Applied Materials • Santa Clara, CA

8d • Onsite

About The Position

Applied Materials is hiring a Data Scientist Intern for its Supply Chain Analytics team in Santa Clara, California. 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, what the underlying data represents, and how decisions are made, then apply analytical methods and tools to business problems.

The role combines technical work with collaboration. The intern will explore and analyze data, write SQL, develop statistical and machine learning models, contribute to generative AI and LLM initiatives, and design dashboards and reports. They will work with stakeholders to understand challenges and requirements, turn business needs into scalable analytical solutions, and communicate findings to technical and non-technical audiences. The team values strong fundamentals, careful evaluation of AI-generated outputs, curiosity, initiative, and the ability to explain and defend analytical work.

Applicants must be currently pursuing a master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Operations Research, Industrial Engineering, or Supply Chain Analytics. A GPA of 3.0 or above is preferred. The position is a full-time internship for Summer 2027. Travel is not required, and relocation is eligible. Applications are reviewed on a rolling basis; the stated application deadline is December 30, 2026, though the position may close earlier.

Requirements

• Currently pursuing a master's degree in Data Science, Computer Science, Statistics, Operations Research, Industrial Engineering, Supply Chain Analytics, or another quantitative field.
• Working knowledge of databases and data modeling, including RDBMS concepts, normalization, primary and foreign keys, and indexing.
• Working knowledge of SQL, including joins, aggregations, CTEs, and window functions.
• Working knowledge of Python for data analysis, including Pandas, NumPy, and scikit-learn.
• Knowledge of machine learning and statistical fundamentals, including supervised and unsupervised methods, train/test methodology, evaluation metrics, distributions, sampling, and correlation versus causation.
• Coursework or project experience with a cloud data platform and data at scale, such as Databricks, Snowflake, or BigQuery, including distributed processing and partitioning concepts.
• Data visualization experience or knowledge with Tableau and/or Power BI.
• Exposure to data engineering concepts, including ETL/ELT, ingestion from multiple sources, and pipeline design.
• Exposure to generative AI and LLMs, including prompting, retrieval augmented generation, LLM APIs, and output evaluation.

Nice To Haves

• GPA of 3.0 or above.
• Understanding of version control frameworks such as Git and Bitbucket.
• Prior supply chain experience; this is preferred but not required.
• Interest in supply chain or a stated desire to build a career in supply chain and operations.
• A supply chain project taken end to end, from raw data through a result someone actually used.
• 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.
• Ability to learn a new domain quickly, ask questions, turn feedback into better work, investigate data, trace numbers from their origin through to the decisions they inform, collaborate with stakeholders, and take initiative.

Responsibilities

• Learn the supply chain business, its operations, the meaning of its 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 generative AI and LLM initiatives, including AI-powered search, automation, and business applications, and build reusable components where appropriate.
• Design and enhance dashboards and reports using Tableau and/or Power BI.
• Partner with stakeholders to understand business challenges, gather requirements, and identify improvement opportunities.
• 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.
• Potential eligibility for other compensation, such as participation in a bonus and stock award program, as applicable.
• Relocation eligible.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern