Data Scientist IV - (B4)

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

Salary:

$170,000.00 - $234,000.00

Location:

Santa Clara,CA

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. 

About the Role
We are seeking a forward‑thinking Data Scientist focused on operational optimization and intelligent automation. The ideal candidate will leverage machine learning, statistical modeling, and emerging agentic AI capabilities to transform complex data into actionable insights and autonomous workflows that drive measurable impact across business operations.

Responsibilities

• Optimize operational workflows by designing and deploying ML models that improve efficiency, reduce manual effort, and support data‑driven decision-making across business units.
• Develop autonomous, agentic AI systems that can proactively monitor processes, make recommendations, trigger actions, and continuously improve through feedback loops.
• Interpret and analyze complex datasets using advanced statistical and machine learning techniques; communicate insights clearly to technical and non‑technical stakeholders.
• Build scalable data collection and analytics pipelines that enhance data quality, statistical efficiency, and real-time decisioning.
• Develop and validate custom ML models (supervised, unsupervised, time-series, causal inference, etc.) tailored to operational use cases.
• Implement predictive and prescriptive models to address a wide range of business challenges in manufacturing, supply chain, customer operations, finance, and more.
• Work with cross-functional teams to define new process automation and optimization opportunities driven by machine learning and intelligent agents.
• Maintain and enhance internal data systems, ensuring ongoing data integrity, reliability, and governance.
• Participate in code reviews, model reviews, and best‑practice development, contributing to a high-performance Data Science culture.

Requirements

• Strong expertise in data modeling, database design, feature engineering, and data mining with large-scale structured and unstructured datasets.
• Proficiency with SQL, statistical programming languages (Python, R) and experience building end-to-end ML workflows.
• Hands-on experience with machine learning algorithms and frameworks, including clustering, decision trees, ensemble methods, deep learning, and reinforcement learning.
• Familiarity with agentic AI frameworks, autonomous decision agents, and LLM-based workflow orchestration (e.g., tools, function-calling, planning agents).
• Experience with Tableau or similar BI tools, enabling clear, actionable data storytelling.
• Expertise in statistical techniques including regression, distribution properties, hypothesis testing, and experimental design.
• Strong analytical and problem‑solving skills with exceptional attention to detail, data accuracy, and model validation rigor.
• Ability to systemically identify optimization opportunities and translate them into scalable ML or AI-driven automation solutions.
• Deep experience writing highly optimized SQL queries and working with large enterprise data systems.

Qualifications / Experience

• Master’s Degree in Computer Science, Data Science, Statistics, Engineering, or a related field.
• 4–7 years of relevant industry experience in applied machine learning, data science, operational analytics, automation, or AI agent development.

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

No

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

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.

In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.