Data Scientist - Agentic AI / ML at Applied… · Santa…

Summary: Applied Materials is a global leader in materials engineering solutions, seeking a Data Scientist to join their Joint Operations Leadership Data Science team. The role involves developing analytical models and AI solutions to drive operational excellence and enhance business operations through advanced analytics and machine learning. Responsibilities: - Works in project teams developing difficult analytical models, algorithms and automated processes, research and develop machine learning models from inception to deployment - Work on GenAI and LLM projects, including fine-tuning models, creating embedding-based search systems, and developing AI-driven prototypes to enhance business operations - Directing architects to design and solution GenAI architectures for stakeholders, specifically for plugin-based solutions and custom GenAI application builds - Use data mining and machine learning algorithms to provide insights into historical and real-time data for projects such as material forecast, demand forecast, pattern recognition, etc - Interfaces with stakeholders for requirements analysis and special requests and schedules; derives insights and works with business units to determine actions and KPI for those actions - Identify opportunities for forecast accuracy improvement and provide business insights and additional perspectives to Service Supply Chain leadership - Collaborate with Material Planning, Field Operations, Inventory Management, NPI, Production Demand Planning, Reliability Engineering, Service Campaigns Teams to gather data and bring information on key business drivers that impact the future demand on Service Parts and Accessories Required Qualifications: - Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research) - 0-2 years of industry experience in applied machine learning or related AI work - Hands-on experience building GenAI-focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated - Can work collaboratively with cross-functional teams - Hands-on experience with building GenAI-focused application and applying LLMs and agentic AI (e.g., agents, reasoning workflows, or RAG) - Have personally implemented models in common Deep Learning frameworks such as PyTorch, Jax or TensorFlow - MLOps, including model deployment, versioning and performance monitoring in production environments - Proficiency in Python, SQL, and tools such as scikit-learn, and forecasting libraries - Excellent analytical and problem-solving abilities, Machine Learning Concepts - Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders Required Skills: Applied Machine Learning, Artificial Intelligence, Generative AI, Large Language Models, Deep Learning Frameworks, PyTorch, Jax, TensorFlow, MLOps, Model Deployment, Model Versioning, Model Performance Monitoring, Python, SQL, Scikit-learn, Forecasting Libraries, Analytical Skills, Machine Learning Concepts Benefits: Comprehensive benefits package, Participation in a bonus and a stock award program