Data Analyst

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.

KLA has manufacturing sites across the globe, including Belgium, China, Germany, Israel, Singapore and Milpitas (CA). The Global Operations (GOPS) team, comprised of Manufacturing, Supply Chain Management, Manufacturing Engineering, Installation, and Quality, is responsible for manufacturing our leading-edge technology. We partner with our world-wide supply base and our design engineering teams to bring new products to market. The GOPS team is continuously working to build our products Better, Faster, Cheaper.

Job Description/Preferred Qualifications

The Operations Data Analyst is responsible for the design and development of analytics products to support the Data Democratization efforts. Analytics democratization refers to the process of making analytics accessible and usable by a wider range of people within an organization, not just data experts or analysts. This empowers non-technical employees to explore data, gain insights, and make informed decisions without relying heavily on IT or specialized tools, and deploy a regional Analytics Product in the production environment. 

•    This is an enabling Role to support Global Operations (Purchasing, Planning, Master Scheduling, Manufacturing, and Quality) with Analytics Products (Snowflake, Power-BI)
•    This is a single contributor member of a multi-disciplinary team with common goals.
•    Create clear and concise data visualizations (charts, graphs, dashboards using Power BI) to communicate insights to stakeholders and decision-makers.
•    Develop Analytics using statistical methods, heuristics, and ML Models. 
•    Develop project plans and timelines for Analytics Products 
•    Function as liaison between the business (Operations) and the IT organization (Snowflake, Power BI, and Software Developers)
•    Support the global effort for Analytics Democratization
•    Prepare the Business Requirement Document for Analytics project.
 

Skills

• Proficiency in SQL (or Snowflake) for data extraction and manipulation.
• Programming languages like Python is necessary.
• Expertise in data visualization tools (e.g., Tableau, Power BI)
• Ability to work in a multicultural team, and with groups located in other regions like: US, Israel, Singapore, Wales, and Germany
• Ability to communicate complex subjects in simple terms is fundamental.
• Ability to work in multiple projects at the same time.

Education an Experience

• Bachelor's degree in statistics, mathematics, computer science, industrial engineering, or a related field 
• 2- 4 years of Proven experience in data analysis and reporting using data analytics tools, and working on Cloud based Data Warehouse (Preferred Snowflake)
• Excellent project Management Skills, with experience on leading and executing Analytics Products

Minimum Qualifications

We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.

KLA is proud to be an equal opportunity employer

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