At Zoox, our Logistics and Service Operations teams build the scalable, efficient processes that keep our autonomous fleet moving. As our Senior Service Parts Forecasting Manager, you will drive proactive parts availability across all service centers—ensuring the right components are exactly where they need to be, before they are ever needed. You will build and own the forecasting systems, data models, and planning processes that maximize fleet uptime, mitigate supply chain risk, and enable Zoox to scale with confidence.
Joining a passionate team at the intersection of logistics, data analytics, and fleet operations, you will be given significant autonomy. This role offers a unique opportunity to establish a best-in-class forecasting discipline from the ground up within one of the most innovative companies in the mobility space.
In this role, you will:
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Own the spare parts demand forecasting model using consumption data, telemetry, and failure trends to develop proactive replenishment plans that minimize fleet downtime.
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Build predictive planning dashboards and track KPIs (forecast accuracy, parts availability) to monitor inventory health and present actionable insights to senior leadership.
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Identify supply risks (lead time changes, EOL parts, shortages) and provide accurate long-range demand signals to suppliers to drive mitigation strategies.
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Partner cross-functionally with Engineering, Fleet Operations, and Supply Chain to incorporate vehicle changes and new parts into the demand plan.
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Drive alignment on inventory investment decisions, balancing high service-level attainment against working capital efficiency.
Qualifications:
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Bachelor's degree in Supply Chain, Industrial Engineering, Data Science, Business Operations, or a related field.
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5+ years in demand forecasting, inventory planning, or supply chain analytics within a service parts or aftermarket environment.
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Proficiency in statistical modeling, time-series analysis, and predictive analytics applied to spare parts or MRO inventory.
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Strong data analytics skills (SQL, Python, R, or equivalent) to build and maintain forecasting models from complex datasets.
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Experience with ERP and inventory management systems (SAP preferred).
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Exceptional cross-functional collaboration skills, with the ability to translate complex analytical outputs into executive-ready recommendations in a fast-paced environment.
Bonus Qualifications:
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Master's degree in a related field and/or industry-recognized supply chain certifications (APICS CPIM, CSCP, or equivalent).
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Experience in the automotive, autonomous vehicle, or aerospace industries, particularly supporting high-mix, low-volume parts or new city launches.
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Familiarity with machine learning techniques for demand sensing and experience with advanced planning systems (Kinaxis, o9, Blue Yonder, etc.).
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Proficiency in data visualization tools (Tableau, Power BI, Looker) to enhance reporting and inventory health dashboards.