Data Scientist positions focus on delivering results in their domain. This page aggregates open Data Scientist roles and what employers typically expect.
## **The group you’ll be a part of** In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam’s etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry. ## **The impact you’ll make** Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You will develop algorithms and automated processes to evaluate large data sets from disparate sources, enabling informed, data‑driven decisions across the organization. In this role, you will leverage your computer science expertise and experience working with large-scale data to solve real-world scientific and engineering challenges in cutting-edge semiconductor manufacturing and research. Your work will directly impact how complex problems are understood, diagnosed, and solved in highly advanced processing environments. This role requires a strong curiosity for how physical systems behave and a motivation to apply data science methods to uncover underlying mechanisms. You will work at the intersection of data, science, and engineering, helping translate complex data into meaningful insights that drive both immediate problem-solving and long-term innovation. ## **What you’ll do** This position is for a Data Scientist within the Selective Etch Product Group, part of the Global Product Group, based in Fremont, CA. The team supports existing products in the field and plays a critical role in the development and market introduction of new selective etch technologies. In this role, the Data Scientist will analyze large and complex data sets and develop advanced analytics algorithms to support Lam’s Selective Etch equipment. The work directly enables faster problem resolution, improved product reliability, and data‑driven decision‑making across engineering teams. Key responsibilities include: - Customer Escalations & Root Cause Analysis When addressing a customer escalation, the Data Scientist will partner closely with subject matter experts to understand the problem, identify available data, perform quantitative analysis, interpret results, and clearly communicate insights to the broader engineering team. - Analytics Tools & Applications Develop analytics applications with intuitive, user‑friendly interfaces that enable engineers—without programming expertise—to diagnose and troubleshoot similar issues efficiently in the future. - Predictive Analytics & Failure Prevention Design and implement algorithms that identify trends and signals in tool and process data to help predict potential failures before they occur, improving uptime and customer confidence. ## **Who we’re looking for** - Bachelor’s degree + 2years experience or Master's degree in Data Science, Statistics, Computer Science, Engineering, Applied Mathematics, or a related quantitative field. - Strong foundation in data analysis, statistical modeling, and machine learning, with the ability to apply these methods to real‑world engineering problems. - Hands‑on experience programming in Python (required), including common data science libraries (e.g., NumPy, pandas, SciPy, scikit‑learn, PyTorch, TensorFlow, or similar). - Experience working with large, noisy, and heterogeneous datasets, including data cleaning, feature extraction, and validation. - Ability to translate ambiguous problem statements into well‑defined analytical approaches and actionable insights. - Strong communication skills, with the ability to explain technical results clearly to audiences with varied levels of technical expertise. ## **Preferred qualifications** - Experience applying data science techniques in complex industrial environments. - Familiarity with equipment health monitoring, fault detection and classification (FDC), predictive maintenance, or time‑series analysis. - Experience developing analytics tools or application…