Summer 2027 Data Scientist Intern - Master's (Santa Clara, CA)
About The Position
Applied Materials is seeking a Data Scientist Intern to join 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 and what the underlying data represents, then develop analytical solutions that support business decisions. This role combines technical work with collaboration: candidates should use AI tools to work efficiently while maintaining strong fundamentals, validating assumptions, and being able to explain and defend their work. The internship includes exploratory data analysis, SQL-based data extraction and analysis, development of statistical and machine learning models, contributions to GenAI and LLM initiatives, and creation or enhancement of dashboards and reports. The intern will work with stakeholders to understand business challenges, translate needs into technical requirements, and communicate findings to technical and non-technical audiences. Applicants must be pursuing a master's degree in a quantitative field. Applications are reviewed on a rolling basis; apply by December 30, 2026. The position may close earlier based on application volume or candidate selection.
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.
- Experience with data visualization using Tableau and/or Power BI.
- Ability to learn a new domain quickly, ask questions, and incorporate feedback.
- Ability to investigate data, trace figures from source processes through tables to decisions, and engage stakeholders to clarify the decisions work should support.
- Proactive approach and willingness to take initiative.
Nice To Haves
- GPA of 3.0 or above preferred.
- Exposure to data engineering concepts, including ETL/ELT, ingestion from multiple sources, and pipeline design.
- Exposure to GenAI and LLMs, including prompting, retrieval augmented generation, LLM APIs, and output evaluation.
- Understanding of version control frameworks such as Git and Bitbucket.
- Prior supply chain experience 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 completed end to end, from raw data through something 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.
Responsibilities
- Learn how supply chain operations run, what the underlying data represents, 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 the work can scale.
- Design and enhance dashboards and reports using Tableau and/or Power BI.
- 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 and a stock award program, as applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
