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:

This role focuses on strengthening and scaling current AI-driven solutions in supply chain and spares execution, with an emphasis on delivering measurable business impact through advanced analytics and intelligent systems. The Data Scientist will work on high-impact projects involving structured and unstructured data, statistical modeling, and machine learning to enhance forecasting, planning accuracy, and operational decision-making. In addition to supporting today’s priorities, the role will contribute to the team’s long-term vision by exploring emerging AI technologies, including Generative AI and Large Language Models (LLMs), to ensure readiness for future innovation.

• Collaborate with cross-functional teams to design and develop advance AI solutions for high value problems in supply chain and planning

• Apply advanced statistical and machine learning techniques to extract insights andoptimizeplanning, forecasting, and operational efficiency.

• Build andmaintainscalable data pipelines and analytical models using tools like Python, SQL, and cloud-native technologies.

• Interface with internal stakeholders to gather requirements, define KPIs, and translate insights into actionable business strategies.

• Lead the development and deployment of LLMs and Generative AI solutions tailored to supply chain and planning challenges

• Experiment withcutting-edgetechniques such as RAG,LoRA, and prompt engineering to build intelligent agents and decision-support systems.

Requirements

• Masters Degree in Data Science, Computing, AI/ Analytics

• 7-10 years of deepexpertisein machine learning, NLP, and transformer-based architectures.

• Proficiencyin Python, SQL, and ML frameworks (e.g.,PyTorch, Hugging Face).

• Familiarity withMLOpstools and cloud platforms (Azure preferred).

• Strong understanding of supply chain, planning, and operational workflows.

• Ability to align technical solutions with strategic business goals and KPIs.

• May lead technical initiatives or mentor peers in AI experimentation and deployment.

• Drives innovation byidentifyingnew opportunities for generative AI across the organization.

• Tackles complex, ambiguous problems using analytical thinking, experimentation, and domain knowledge.

• Develops scalable solutions that adapt to evolving business needs.

• Contributes directly to the success of AI initiatives that improve efficiency, accuracy, and agility in global operations.

• Communicates technical concepts clearly to both technical and non-technical stakeholders.

Additional Information

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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.