At a glance

Location: Austin, TX
Work type: Onsite
Start: Summer 2027
Category: Data

What they are looking for

SqlPythonTableauPower biPandas

Location: Austin,TX

Who We Are

Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer

Location

Austin,TX

You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

TEAM OVERVIEW

Join our dynamic Supply Chain Analytics team as a Data Scientist Intern! Our mission is to revolutionize efficiency by harnessing the power of machine learning, statistical and simulation modeling, generative AI, and actionable insights.

We are dedicated to transforming process efficiency through deep analysis, cutting-edge visualization, and enhanced UI/UX. Our goal is to elevate decision support systems and measurement capabilities, driving substantial improvements in key business metrics. Be a part of our journey to make a significant impact!

HOW WE WORK

AI has changed how fast a data scientist can move. It has not changed what makes one good.

We look for people who use AI tools aggressively to move faster, and who can still explain every line they ship, defend the assumptions behind a model, and recognize an answer that is fluent but wrong. Strong fundamentals first, AI as a multiplier.

KEY RESPONSIBILITIES

Learn the business: how our supply chain operations run, what the underlying data represents, and where decisions get 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, building reusable components where the work can scale.

Design and enhance dashboards and reports using modern tools (Tableau, Power BI, or Custom built).

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 both technical and non-technical audiences.

TECHNICAL SKILLS

Required Foundations

Coursework or hands-on experience with databases and data modeling (RDBMS concepts, primary and foreign keys, table relationships, basic normalization).

Working knowledge of SQL (joins, aggregations, subqueries; CTEs and window functions a plus).

Working knowledge of Python for data analysis (Pandas, NumPy).

Introductory statistics and machine learning fundamentals (supervised versus unsupervised methods, train/test split, basic evaluation metrics, distributions, correlation versus causation).

Familiarity with data visualization using Tableau, Power BI, or a comparable tool.

Bonus: Tooling and AI Experience

Exposure to data engineering concepts (ETL/ELT, ingestion from multiple sources, pipeline design).

Exposure to GenAI and LLMs (prompting, retrieval-augmented generation, LLM APIs, output evaluation).

Understanding of version control frameworks such as Git and Bitbucket is a plus.

Coursework or project experience with a cloud data platform and data at scale (Databricks, Snowflake, or BigQuery; distributed processing and partitioning concepts).

REQUIREMENTS / EDUCATION

Currently pursuing a Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, Supply Chain Analytics, or another quantitative field.

GPA of 3.0 or above preferred.

IDEAL CANDIDATE

The ideal candidate learns a new domain quickly, asks questions, and turns feedback into better work. This role is equally technical and collaborative, and strong technical skills alone will not carry the work. Prior supply chain experience is preferred but not required. Curiosity about how a global supply chain works matters more, and you will learn the domain here.

You are someone who

Investigates the data instead of accepting it, and asks the question behind the question.

Traces a number end to end - from the process that generated it, to the table it lands in, to the decision it drives.

Partners with stakeholders instead of taking requirements at face value, and asks what decision the work needs to support.

Is proactive and takes initiative.

Has a growth mindset.

ADDED ADVANTAGE

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 something someone actually used.

Class or personal projects using LLM applications (RAG pipelines, agents, or evaluation harnesses).

Public portfolio such as GitHub, Kaggle, or Tableau Public demonstrating applied projects.

Applications will be reviewed on a rolling basis. Please apply by November 30, 2026. Note: This position may close early based on application volume or candidate selection.