Data Scientist

KLATencor Corporation • Ann Arbor, MI • 2h ago

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.

We are seeking an experienced and highly motivated Data Scientist III to join our Business Intelligence team. This role will apply advanced analytics, statistical modeling, machine learning, and optimization techniques to solve complex business and supply chain problems and improve data-driven decision-making. The successful candidate will work closely with business and technical stakeholders to translate ambiguous business challenges into analytical frameworks, develop models and decision-support tools, and communicate findings in a way that drives action. The position will also play an important role in the development and analysis of key performance indicators (KPIs), helping the organization better understand the drivers of operational and customer-facing performance. This role is well suited for someone who combines strong statistical and technical capabilities with business curiosity and practical problem-solving skills. The Data Scientist III will have opportunities to work across the analytical lifecycle, from exploratory analysis and experimentation through modeling, optimization, deployment, and ongoing performance monitoring. Key Responsibilities:Advanced Analytics & Data Science

Develop statistical and machine learning models to address complex business and supply chain challenges.

Apply techniques such as regression, classification, forecasting, simulation, clustering, and other statistical or machine learning methodologies as appropriate to the business problem.

Design analytical approaches for problems involving uncertainty, complex relationships, and large or heterogeneous datasets.

Evaluate model performance, assumptions, limitations, and business applicability to ensure analytical solutions are both technically sound and practically useful.

Perform exploratory and diagnostic analyses to identify trends, relationships, risks, and opportunities within business and operational data.

Optimization & Decision Science

Develop optimization models and decision-support engines that translate business objectives, constraints, and analytical insights into recommended actions.

Apply approaches such as mathematical optimization, simulation, statistical modeling, and algorithmic decision-making to supply chain and operational problems.

Partner with business stakeholders to define objective functions, constraints, trade-offs, and measures of success.

Evaluate alternative strategies through scenario analysis and quantify their expected operational or business impact.

KPI Development & Performance Analytics

Design, develop, and analyze KPIs and performance measurement frameworks.

Partner with stakeholders to translate strategic and operational objectives into measurable indicators.

Conduct deeper analysis beyond KPI reporting to identify underlying drivers of performance and opportunities for improvement.

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