In Demand Tech Jobs in Rohnert Park, CA (NOW HIRING)

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Keysight Technologies is seeking an experienced Supply Chain Analyst to join our team managing supply chain functions for our world-class technology centers. The ideal candidate will have a strong background in supply chain management, with a focus on business process optimization, program management, and project management. This role will involve overseeing and improving supply chain processes, Leading cross-functional programs, and ensuring the successful implementation of supply chain initiatives to support business growth and efficiency. Additionally, the role will include developing reports and dashboards, and some coding in SQL or Python to manage information access and analysis.

Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

Keysight is seeking a Supply Chain Analyst to support the R&D, New Product Introduction (NPI), and production operations of our internal technology centers. This role may support either the High Frequency Technology Center (HFTC), which delivers semiconductor and RF/microwave device technology, or the Precision Machining Technology Center (PMTC), which delivers mesoscale precision machining and specialty fabrication across multiple sites. Depth in one domain with a willingness to learn the other is expected.

Both portfolios operate in a high-mix, low-volume ecosystem characterized by high demand variability, long and constrained supply lines, and shared capacity competing across research, prototype, qualification, and production builds. Both also sit upstream in a deeply vertically integrated supply chain, where variability at the technology center propagates directly into downstream product availability. The successful candidate will bring analytical rigor and project leadership to material availability, capacity planning, supplier performance, and process improvement - building repeatable, automated capability rather than one-off analysis.

• Own material availability and supply readiness for R&D, NPI, and production demand streams, including long-lead item identification, risk buys, and escalation of constraints that threaten program schedules.
• Build and maintain analytical models and automated reporting for demand, inventory, capacity, cost, and supplier performance - replacing manual spreadsheets with sustainable, self-service tools.
• Partner with R&D, process and manufacturing engineering, quality, finance, and procurement to align material and capacity plans to program milestones and release schedules.
• Lead and coordinate supply chain projects and continuous improvement initiatives from problem definition through implementation, measurement, and sustaining handoff.
• Develop prioritization and allocation frameworks for constrained materials, equipment, and supplier capacity shared across competing R&D, NPI, and production demand.
• Manage supplier relationships and performance for specialty materials and qualified outside processing, including scorecards, delivery and quality metrics, cost analysis, and negotiation support.
• Assess and mitigate supply risk - sole-source exposure, obsolescence and end-of-life, geopolitical and trade disruption, and capacity concentration - with documented contingency plans.
• Support prototype-to-production transitions, including qualification builds, first-article and process qualification requirements, and yield and scrap learning curves.
• Improve master data quality and planning parameter discipline (lead times, safety stock, reorder points, lot sizing) across a part population with substantial legacy and one-off content.
• Present findings, trade-offs, and recommendations clearly to technical teams and to management.

#LI-MO1

• Bachelor's degree in Supply Chain, Engineering, Business, or a related field, with 3-5+ years of experience in supply chain, materials management, or operations planning.
• Manufacturing supply chain experience in a technically complex, low-volume environment - semiconductor, precision machining, aerospace, medical device, or scientific instrumentation.
• Excellent communication and presentation skills, including the ability to translate complex supply data into clear recommendations for engineering, operations, and executive audiences.
• Strong analytical and problem-solving skills, with a demonstrated ability to work from incomplete, inconsistent, or messy data sets.
• Ability to lead and coordinate cross-functional and cross-site supply chain projects from definition through implementation.
• Experience with business process optimization and improvement using a structured methodology (Lean, Six Sigma, or equivalent).
• Proficiency in program and project management, including phase-gate/NPI processes, risk registers, and schedule-to-material alignment.
• Ability to work independently and within cross-functional teams spanning R&D, engineering, operations, quality, finance, and procurement.
• Experience in analytics and modeling using tools such as Python, SQL, Power BI, Power Apps / Power Automate, or advanced Excel - able to build and maintain automated solutions, not just one-off analyses.
• Working knowledge of ERP/MRP systems (SAP or equivalent) and PLM/BOM structures, including engineering change management, revision control, and part lifecycle status.

These apply equally to both technology center portfolios and are central to success in this role.

• Demonstrated ability to plan material where lot sizes are small, demand is lumpy, and statistical forecasting alone is insufficient - comfort with consumption-based, project-based, and judgment-driven planning methods.
• Experience balancing R&D, NPI, and production demand competing for the same constrained equipment, suppliers, and skilled labor, including prioritization frameworks and escalation paths.
• Understanding of setup-dominated capacity models, where changeover and qualification time - not run time - drives throughput and lead time.
• Ability to structure and maintain part, supplier, and process data where master data quality is inconsistent and legacy or one-off part numbers are common.
• Familiarity with make/buy analysis and internal-versus-external capacity trade-offs for specialty processes.
• Comfort operating in ambiguity and building new processes where none exist - this role supports evolving R&D and NPI operations, not a fully mature production line.

Candidates are expected to bring depth in one of the following areas. Experience in both is a differentiator.

• Compound semiconductor and RF/microwave supply chains: wafers and substrates (GaAs, InP, GaN), mask and reticle sets, epitaxial services, and specialty process chemicals and gases.
• Understanding of how variability originating at the device level propagates downstream through a deeply vertically integrated supply chain - from wafer start and die output into module, subassembly, and finished instrument builds - and the ability to quantify that exposure for downstream product owners.
• Experience positioning buffers and inventory at the right stage of the internal value chain (wafer, die bank, packaged device, module) to absorb upstream yield and cycle-time variability without over-committing capital, including known-good-die and die banking strategies.
• Ability to translate fab and outsourced partner performance - yield, cycle time, and delivery variability at foundry and assembly-and-test partners - into credible downstream commit dates and risk statements for product programs.
• Cleanroom and fab operations concepts: lot travelers, WIP staging, yield and rework loops, and process qualification and requalification.
• Management of long-lead, allocated, or end-of-life semiconductor components, including last-time-buy analysis and alternate-source qualification.
• Familiarity with wafer-level cost roll-ups and yield-adjusted material planning.

• Internal portfolio management across a shared machining capability set - evaluating incoming R&D, NPI, and production work packages against internal capability and available capacity, and making informed load-versus-outsource decisions as the demand mix shifts.
• Capacity modeling for setup-intensive machining operations: machine-hour and operator-hour loading, changeover and queue time, finite-capacity and scenario modeling, and identification of the bottleneck work centers that drive quoted lead time.
• Synchronization of work across three machining fabrication sites - allocating jobs by capability, capacity, and proximity to the internal customer; managing inter-site transfers and WIP visibility; and maintaining consistent planning parameters, routings, part data across all sites.
• Ability to model how site loading, routing choices, and inspection and metrology capacity (first article inspection, CMM) constrain schedule commitments to downstream product programs, not solely quality outcomes.
• Job-shop scheduling concepts: finite capacity, queue time, dispatch prioritization, and machine and operator constraint modeling.

• Demand and inventory modeling: safety stock optimization, reorder point setting, MRP parameter tuning, and scenario or what-if analysis.
• Familiarity with modern AI tooling in a business context - large language model assistants, AI-enabled features within Microsoft 365 and the Power Platform, and AI-assisted code or query generation - used to accelerate analysis, documentation, and process automation.
• Operations and Supply Chain performance management - scorecards, on-time-delivery and quality metrics, cost and should-cost analysis, and negotiation support.
• Familiarity with trade compliance and export control requirements (ITAR/EAR), plus RoHS/REACH and conflict minerals reporting.
• Experience with S&OP / SIOP or an equivalent demand-supply balancing cadence.
• Working knowledge of Smartsheet, Tableau, or similar collaboration and visualization platforms.
• APICS CPIM or CSCP, PMP, or Lean Six Sigma certification.

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