Logistics Data Scientist

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. 

What We Offer

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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. 

Key Responsibilities

• Works in cross-functional project teams as a subject matter expert to design and develop advanced AI-driven solutions leveraging structured and unstructured “big data” sources.

• Partners with BI and analytics teams to align AI initiatives with business goals and ensure seamless integration into dashboards and reporting workflows.

• Develops and implements AI/ML models, including generative AI, LLM-based applications, and retrieval-augmented generation (RAG) pipelines.

• Builds and optimizes LangChain, LangGraph, and similar frameworks for orchestration of large language models and intelligent agents.

• Performs ad-hoc statistical and data-mining analysis using tools such as Python, R, SAS, MATLAB, and SQL; designs scalable data acquisition systems and architectures.

• Creates automated workflows for data ingestion, cleansing, integration, and evaluation of large datasets.

• Interfaces with internal customers for requirements analysis and compiles data for scheduled or special reports and analysis.

• Generates internal and external documentation, dashboards, presentations, and technical reports for stakeholders.

• Explores emerging technologies and frameworks to drive innovation in AI engineering and advanced analytics.

• Serves as a resource and provides guidance to team members on AI engineering best practices, data science methodologies, and cutting-edge tools.

Functional Knowledge

Demonstrates conceptual and practical expertise in data science, AI/ML engineering, and LLM orchestration frameworks, with basic knowledge of related disciplines such as software engineering and business analytics.

Business Expertise

Has knowledge of best practices and how AI and data science integrate with business operations; is aware of competitive trends and emerging technologies shaping the industry.

Leadership

Acts as a resource for colleagues with less experience; may lead small AI-focused projects with manageable risks and resource requirements.

Problem Solving

Solves complex problems using innovative approaches; takes a new perspective on existing solutions; exercises judgment based on analysis of multiple sources of information.

Impact

Impacts a range of customer, operational, project, or service activities within own team and other related teams; works within broad guidelines and policies.

Interpersonal Skills

Explains difficult or sensitive information clearly; works to build consensus across teams.

Education & Experience

• Education: Bachelor’s Degree (Master’s preferred in Data Science, AI/ML, Computer Science, or related field)

• Experience: 4–7 years in data science, AI/ML engineering, and advanced analytics.

Preferred Skills

• Proficiency in Python, R, SQL, and experience with big data platforms (e.g., Spark, Databricks).

• Hands-on experience with LangChain, LangGraph, and orchestration of LLM-based applications.

• Familiarity with cloud environments (AWS, Azure, GCP) and containerization (Docker, Kubernetes).

• Strong understanding of AI/ML frameworks (TensorFlow, PyTorch) and prompt engineering.

• Knowledge of retrieval-augmented generation (RAG), vector databases, and API integrations.

• Excellent communication and stakeholder management skills.

• A curious, experimental mindset with passion for exploring emerging technologies.

Additional Information

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Relocation Eligible:

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.