Lam Research is looking for a Data Scientist to analyze unstructured and diverse big data into actionable insights, develop algorithms and automated processes to evaluate large data sets from disparate sources, and enable informed and data-driven decisions.
Requirements
- Machine Learning Expertise: Strong theoretical foundation and hands-on experience in ML algorithms, deep learning, AI, statistics, or optimization.
- Programming Skills: Proficient in Python, with motivation to write efficient, maintainable, testable, and well-documented code.
- ML Frameworks: Experience with modern ML frameworks such as PyTorch, JAX, or TensorFlow.
- Domain expertise in semiconductor engineering, Bayesian statistics, process engineering, multi-physics modeling, or numerical simulation.
- Familiarity with Linux/Unix operating systems.
- Experience with MLOps tools and principles (e.g., Docker, CI/CD pipelines).
Responsibilities
- Analyze large, complex datasets from diverse sources to uncover insights and identify opportunities for innovation.
- Design, build, and deploy robust machine learning models with meaningful uncertainty quantification.
- Perform rigorous data engineering and model evaluation, including feature engineering, hyperparameter tuning, and model selection.
- Collaborate with engineering teams to integrate models into production codebases, promoting best practices in code quality and maintainability.
- Communicate findings and technical results clearly to both technical and non-technical stakeholders.
Other
- Master’s degree with 6+ years of experience or Ph.D. with 3+ years in Computer Science, Engineering, Physics, Applied Mathematics, Statistics, or a related quantitative field.
- Problem Solving: Demonstrated analytical and critical thinking skills, with a track record of delivering impactful R&D solutions.
- Team Collaboration: Proven success working in cross-functional teams with strong execution and communication skills.
- Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
