Data Scientist- Install Automation

Applied Materials • Austin, TX

12d • $78,500 - $108,000 • Onsite

About The Position

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.

Requirements

• Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or related field.
• 3+ years of experience in Data Science, Machine Learning, AI, Advanced Analytics, or Process Automation.
• Strong proficiency in Python and machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, or equivalent.
• Experience developing predictive models, optimization algorithms, recommendation systems, or workflow automation solutions.
• Knowledge of supervised and unsupervised learning, deep learning, Generative AI, and statistical modeling.
• Experience working with large-scale engineering, manufacturing, service, or operational datasets.
• Semiconductor equipment, industrial automation, or field service experience preferred.
• Strong analytical, problem-solving, and communication skills with the ability to translate complex data into business value.
• Willingness to travel internationally (approximately 10%).

Responsibilities

• Develop and deploy AI, machine learning, and analytics solutions to support Install Automation, Auto Sequencing, Smart Sequencing, and task automation initiatives.
• Build predictive and optimization models that improve installation efficiency, resource utilization, workflow execution, and cycle-time performance.
• Analyze engineering, installation, service, and operational data to identify patterns, predict outcomes, and drive automation decisions.
• Design and implement data pipelines, feature engineering, model training, validation, deployment, and monitoring processes.
• Apply machine learning, optimization techniques, and Generative AI to automate engineering workflows, documentation, and decision-making.
• Create dashboards and KPI frameworks to measure automation effectiveness, productivity improvements, and business impact.
• Partner with Engineering, Manufacturing, Service, and Digital Transformation teams to develop and scale enterprise automation solutions.
• Document methodologies, models, and best practices to support adoption across global teams.

Benefits

• Supportive work culture that encourages learning, development, and career growth.
• Programs and support that encourage personal and professional growth.
• Comprehensive benefits package.
• Potential eligibility for other forms of compensation such as participation in a bonus and a stock award program.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level