Group/Division
KLA has manufacturing sites worldwide. The Global Operations (GOPS) team, comprised of Manufacturing, Supply Chain Management, Manufacturing Engineering, Installation and Quality, builds our leading-edge technology. GOPS partners with KLA's global supply base and design engineering teams to develop new products, working continuously to build better, faster and more cost-efficient solutions.
Responsibilities
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 looking for a data- and programming-oriented student to drive process improvement and efficiency across the team. In this role you will:
•Plan and deliver dashboards and a variety of visualizations to profile and analyze data
•Develop automated systems and end-to-end processes
•Proactively identify issues and gaps within the team
•Collaborate effectively with diverse stakeholders across different roles
You will work with tools such as Python, SQL, Streamlit, Power BI, and Excel (Macros/VBA), and are expected to initiate, evaluate, and adopt new tools and approaches—bringing curiosity, initiative, and an open mind to continuously enhance our data products and workflows.
Requirements
•B.Sc. in Information Systems, starting 3rd year of studies
•Availability for at least 2.5 days per week
•High-level proficiency in Python
•Knowledge of SQL
•Understanding of data models and database design
•Strong mathematical and analytical skills, with the ability to collect, measure, organize, and analyze data
•Strong problem-solving skills and attention to detail
•Ability to multitask and work effectively in a dynamic environment
•Strong teamwork and collaboration skills
•Strong verbal and written communication skills in English
•Power BI experience – an advantage
About the company
We provide advanced inspection tools, metrology systems, process solutions, and computational analytics that make electronics possible, tackling complex challenges. From electron and photon optics to machine learning and data analytics, we seek perfection at the most fundamental level of matter in the universe.
