This job posting is no longer active
Calling the adventurers ready to join a company that's pushing the limits of nanotechnology to keep the digital revolution rolling. At KLA, we're making technology advancements that are bigger—and tinier—than the world has ever seen.
Who are we? We research, develop, and manufacture the world's most advanced inspection and measurement equipment for the semiconductor and nanoelectronics industries. We enable the digital age by pushing the boundaries of technology, creating tools capable of finding defects smaller than a wavelength of visible light. We create smarter processes so that technology leaders can manufacture high-performance chips—the kind in that phone in your pocket, the tablet on your desk and nearly every electronic device you own—faster and better. We're passionate about creating solutions that drive progress and help people do what wouldn't be possible without us. The future is calling. Will you answer?
The Global Supply Chain (GSC) organization is a matrix organization overseeing sourcing, supplier contracting, supplier management, materials management, procurement (direct and indirect), logistics, and trade compliance around the world. GSC leads the company to establish and manage an innovative, reliable, efficient, effective, and compliant supply chain and logistics, working to assure competitive advantage for KLA.
Spare planning analytics and logistics specialist will be responsible for service parts planning analytics and logistics requirements of the KLA Taiwan Service organization. This position will co-work with HQ parts planning and fulfillment group to assure customer fill rate targets are being effectively achieved, and include supporting various data analytical activities, assuring trade compliance and financial auditing.
Critical thinking and analytical skills - ability to distill large and complex information down to simple, easy to understand data/trends and come to new conclusions based on the findings
Strong attention to detail – Detail oriented and generate KPIs from large datasets. Not only understands the effects, but also the causes and factors the drive these effects