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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist II, New College Grad- Master's (Santa Clara, CA) - **Company:** Applied Materials - **Location:** Santa Clara, CA, United States (Remote available) - **Experience:** Starter - **Salary:** $119,500.0 - $164,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Big Data, BigQuery, Databases, Data Cleansing, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Relational Databases, Database Queries, Decision Support Systems, Distributed Computing Environment, Design of User Interfaces, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NumPy, Query Optimization, Power BI, SciPy, SQL Databases, Tableau (Software), Cloud Platform System, Feature Engineering, Data Ingestion, Large Language Models, Snowflake, Apache Spark, Indexer, Pandas, Scikit Learn, Information Technology, Data Lineage, Data Pipelines, Databricks - **Published:** September 4, 2026 - **Apply:** https://amat.wd1.myworkdayjobs.com/External/job/Santa-ClaraCA/Data-Scientist-II--New-College-Grad--Master-s--Santa-Clara--CA-_R2627771 ## About the Role * Understanding of supply chain management concepts (planning, inventory, logistics, procurement, repair operations, reverse value chain). * Strong database fundamentals (RDBMS concepts, relational and dimensional data modeling, normalization, keys and constraints, indexing, query execution plans). * Strong SQL skills (joins, aggregations, subqueries, CTEs, window functions, query optimization). * Big data fundamentals (distributed processing, partitioning, columnar and table formats, Spark and lakehouse architecture). * Data engineering fundamentals (ETL/ELT, ingestion from multiple source systems, pipeline design and orchestration, data quality and validation). * Strong Python skills for data analysis and machine learning (Pandas, NumPy, SciPy, scikit-learn). * Machine learning fundamentals (supervised and unsupervised methods, feature engineering, cross-validation, evaluation metrics, overfitting and regularization). * Statistical fundamentals (distributions, sampling, hypothesis testing, experimental design, correlation versus causation). * Hands-on experience with Databricks or a comparable cloud data platform (Snowflake, BigQuery). * Data visualization with Tableau and/or Power BI. Applied and AI skills * Applied GenAI and LLM experience (prompting, retrieval augmented generation, LLM APIs, agentic workflows, output evaluation). * Knowledge of Six Sigma, Lean, or DMAIC process improvement methodologies., * Master's degree in Data Science, Operations Research, Engineering, Computer Science, Statistics, Supply Chain Analytics, or another quantitative field. * GPA of 3.0 or above preferred. * Demonstrated skills in data science and business analytics., The ideal candidate takes ownership of a problem, exercises judgment about what is worth building, and sees it through to adoption. This role is equally technical and collaborative, and strong technical skills alone will not carry the work. ## Description Join our dynamic Supply Chain Analytics team as a Data Scientist! 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., * Design, develop, and deploy AI solutions - search, summarization, agentic automation, AI-assisted decision support - built as reusable components and workflows that scale across use cases. * Build the data pipelines that analysis and AI solutions depend on. * Take work from notebook to production, with documented methods, data lineage, and clear ownership. * Build statistical and machine learning models, and evaluate them honestly, including where they fail. * Partner with cross-functional stakeholders to turn ambiguous problems into structured solutions with measurable outcomes. * Build dashboards and applications in Tableau and Power BI that decision makers actually use, and present findings to business and executive audiences., * Knowledge of supply chain circular economy and reverse value chain processes. * Machine learning or AI solutions taken end to end, from data preparation through deployment. * Production LLM application work (RAG pipelines, agents, or evaluation harnesses). * Experience with Databricks ETL, data ingestion, or BI and AI workloads on a governed data platform. 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. ## Related Videos - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [Vectorize all the things! 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