Data Scientist

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 Responsibilities

Data 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, Computer Science, Engineering, Actuarial Science, Economics, or a related field.
• Experience with statistical modeling, machine learning, predictive analytics, or forecasting.
• Strong programming skills in Python and SQL.
• Experience working with large and complex datasets to solve business problems.
• Familiarity with reliability engineering, survival analysis, warranty forecasting, actuarial modeling, or risk analytics is highly desirable.
• Experience rapidly prototyping analytical solutions using modern AI-assisted development tools.
• Strong communication and stakeholder management skills with the ability to connect analytical outputs to business outcomes.
  

Impact

This role directly influences how KLA forecasts service costs, evaluates business risk, and supports critical operational decisions. Success is measured by the ability to develop accurate, scalable analytical models and ensure those insights are effectively adopted within business processes to improve decision quality and operational performance.