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Company Overview
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.Job Description/Preferred Qualifications
A Data Scientist with operations experience leverages advanced analytical methods, statistical modeling, and data engineering skills to improve operational performance and decision‑making across the business. This role partners closely with operations, supply chain, purchasing and planning to identify efficiency opportunities, optimize processes, and develop data‑driven solutions that enhance productivity and scalability.
Key responsibilities typically include designing and maintaining predictive models, building dashboards and performance metrics, analyzing process bottlenecks, and developing automated reporting, and analytic applications or optimization tools.
The role also requires translating complex data insights into clear recommendations for operational leaders, and ensuring data quality, governance, and reliability across operational data pipelines.
An operations‑focused Data Scientist blends technical expertise with strong business and process understanding, enabling them to drive measurable improvements in throughput, cost, quality, and overall operational excellence.
Advanced degree (Master’s) in Data Science, Operations Research, Industrial Engineering, Applied Statistics, Computer Science, or a related quantitative field.
Hands‑on experience with operations‑focused analytics, such as supply chain optimization, forecasting, workforce planning, manufacturing analytics, or process improvement.
- Familiarity with Palantir technologies, including Foundry and Ontology development, with the ability to build, maintain, and operationalize data objects and pipelines in the platform.
Proficiency in statistical modeling and machine learning, including time‑series forecasting, optimization algorithms, clustering, regression, and anomaly detection.
Strong data engineering capabilities, including experience with ETL pipelines, data modeling, and building scalable data architectures.
Experience working with cloud platforms (Azure, AWS, GCP) and modern data stack technologies (Databricks, Snowflake, Synapse, BigQuery, etc.).
Advanced programming skills in Python, SQL, and familiarity with frameworks like PySpark or Spark SQL for large‑scale data processing.
Experience with visualization tools such as Power BI, Tableau, or Looker for building operational dashboards and KPI tracking.
Strong understanding of Lean, Six Sigma, or other continuous improvement methodologies.
Ability to translate complex analytics into clear operational insights for non‑technical stakeholders.
Experience working in cross‑functional environments with operations, product, finance, and engineering teams.
Proven track record of driving measurable improvements in efficiency, throughput, cost reduction, or operational quality.
Minimum Qualifications
Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years; or equivalent work experience
Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.
KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us at [email protected] or at +1-408-352-2808 to request accommodation.
Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to [email protected] to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.
KLA Milpitas, California, USA Office
3 Technology Dr, Milpitas, CA, United States, 95035
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