Data Scientist

To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale-faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology. Group/DivisionThe KLA Services team consists of Service Sales, Marketing, Spares Supply Chain Management, Field Operations, Engineering, Product Training, Digital Solutions and Analytics, and Technical Product Support. Our services organization maximizes the value of our customers' KLA assets - with highly trained service and product support engineers providing installation services and 24/7 technical support and parts delivery through our extensive supply chain network. What You'll Do In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise. Are you passionate about using data to solve complex business challenges and influence strategic decisions? We are seeking a Data Scientist to advance KLA's service cost analytics and forecasting capabilities. In this role, you will develop predictive models and analytical frameworks that help the organization better understand service costs, reliability risk, and long-term financial impact. Working with Service, Engineering, Finance, and Operations stakeholders, you will transform data into actionable insights that improve forecasting accuracy, support business decision-making, and drive operational effectiveness. While the primary focus of this role is advanced analytics and modeling, you will also leverage modern AI-assisted development tools to rapidly prototype lightweight solutions that enable business teams to operationalize analytical insights. Key ResponsibilitiesData Science & Modeling (Primary Focus) Develop predictive models and statistical methodologies to improve service cost forecasting and business planning. Analyze part reliability, failure behavior, service consumption patterns, and installed base trends to identify key service cost drivers. Apply statistical, machine learning, reliability, and actuarial techniques to quantify uncertainty, risk exposure, and long-tail service events. Design scalable analytical frameworks that enable rapid assessment of reliability and cost impacts across products and technologies. Evaluate model performance and continuously improve forecasting accuracy through validation, experimentation, and refinement. Define analytical approaches for solving business problems where historical data may be incomplete, sparse, or highly variable. Business Partnership & Operational Impact Partner closely with Service, Finance, Operations, and Engineering teams to understand business processes, planning workflows, and decision-making needs. Translate business challenges into analytical solutions and ensure model outputs align with operational objectives. Work with stakeholders to identify how predictive insights can be incorporated into forecasting, planning, cost management, and operational decision-making processes. Present findings, assumptions, recommendations, and business impacts to both technical and non-technical audiences. Prototyping & Data Solutions (Secondary Focus) Build lightweight prototypes, analytical tools, and proof-of-concept solutions using AI-assisted development techniques to accelerate insight generation and stakeholder adoption. Develop simple decision-support tools that make analytical models accessible and actionable for business users. Identify opportunities to improve data availability, business processes, and analytical infrastructure to support future modeling capabilities.Preferred Qualifications Master's, or PhD in Data Science, Statistics, Mathematics, Comput