Senior Staff Product Management

Renesas Electronics•Tempe, AZ

1d•Remote

About The Position

We are seeking a Sr. Staff Strategic Capacity PM to own long-term capacity gap identification, provide solution proposals, and lead the initiatives to solve capacity constraints. This role will develop integrated demand/capacity models, maintain internal and external supply chain capacity profiles by site, support surge planning, and lead constraint engineering to identify and solve hidden systemic bottlenecks early enough to align capacity, cost, and DFM actions before NPI start and production ramp. The ideal candidate combines strong quantitative modeling skills, semiconductor supply chain knowledge, constraint engineering discipline, and program management experience to deliver predictable capacity availability at scale, reduce late capacity escalations, prevent surprise bottlenecks at ramp, and connect capacity investment and qualification roadmaps to business needs. Renesas Electronics, a leading global semiconductor company, is rapidly scaling its AI-focused power delivery business. Products include high-performance digital power VRMs, multiphase controllers, Smart Power Stages (SPS), Vertical Power Stages (SPS with integrated capacitors and multiple silicon die), Power Towers (power modules integrating multiple SPS-equivalents with capacitors and inductors), and power MOSFETs.

Requirements

Bachelor’s degree in Operations, Engineering, Supply Chain, or related field.
7+ years of experience in semiconductor manufacturing, supply chain planning, or operations strategy.
Strong understanding of semiconductor fabrication and supply chain with Program Management leadership experience.
Experience identifying systemic bottlenecks, leading data-driven root cause analysis, and driving solutions across engineering, manufacturing, supplier and planning teams.
Advanced analytical and modeling skills (Excel, VCO, AI Optimization, SQL, Python, or similar tools).
Excellent communication and presentation skills.

Nice To Haves

MBA or Master’s degree in Operations, Engineering, Supply Chain or related field.
Strong stakeholder management, communication, collaboration, and partnership skills across Engineering, Operations, Supply Chain, and OSAT partners.
Familiarity with statistical forecasting methods.
Knowledge of industry cycles and long-lead semiconductor equipment planning.

Responsibilities

Develop and maintain component-level demand/capacity models across product lines, technology nodes, manufacturing flows, and planning horizons.
Build scenario-based models for base, upside, downside, and surge demand to support executive capacity decisions.
Establish planning assumptions, model governance, and refresh cadence to improve forecast consistency and decision quality.
Create and maintain supply chain capacity profiles across internal and external manufacturing sites, including front-end, back-end, test, and critical supplier constraints.
Identify structural capacity constraints early and define mitigation paths before NPI start or production ramp commitments.
Support surge planning by modeling practical upside capacity, recovery timing, qualification dependencies, and risk buffers.
Drive fewer late capacity escalations by converting long-range signals into actionable capacity readiness plans.
Identify hidden systemic bottlenecks across design, manufacturing, test, supplier capability, yield, cost, and capacity interfaces before they impact ramp execution.
Lead data-driven root cause analysis using operational, engineering, supplier, yield, and cycle-time data to isolate constraint drivers and quantify business impact.
Program Manage the constraint resolution initiatives from detection through mitigation, closure, and recurrence prevention across cross-functional teams.
Feed structural fixes into DFM, capacity planning, cost reduction, qualification, and supplier readiness roadmaps.
Mitigate systemic scaling failures by converting recurring bottlenecks into durable process, design, sourcing, or capacity solutions.
Facilitate cross-functional capacity reviews to align demand signals, site readiness, supplier capability, and qualification plans.
Conduct sensitivity analysis on demand volatility, supplier constraints, site readiness, surge scenarios, and systemic scaling risks.
Drive continuous improvement in modeling methods, data quality, and planning tools to improve capacity predictability at scale.
Improve recovery speed from issues that do occur by establishing decision paths, mitigation playbooks, and feedback loops into capacity and DFM planning.