Vice President Manufacturing Data Scientist Jobs

The VP, Manufacturing & Production owns the factory system that produces satellites at rate. 

Manufacturing is not a downstream recipient of engineering work at E-Space. The VP, Manufacturing & Production embeds DFM engineers in hardware product teams from PDR onward, participates actively at every program gate, leads production execution through the 100-unit Joint Phase pilot build, and assumes full production ownership at the Manufacturing Readiness Review (MRR). From MRR onward, no other VP can direct the production line without escalating through this role.

The role spans three distinct operating modes: influencing design during the Engineering Phase, demonstrating production readiness during the Joint Phase, and executing at rate during Production. Each requires a different leadership posture.

Production System Ownership

• Own the single metric that defines success: 5 spacecraft/day sustained at or below DTC target
• Assume full production ownership at MRR — from that point, all production line decisions route through this role
• Manage production design changes through the Configuration Control Board (CCB) — ECOs require your concurrence before release
• Provide direct accountability for first-pass yield, automation uptime ≥95%, and ATE fault coverage ≥95%

Product Manufacturing Engineering

• Lead DFM reviews at PDR and CDR; close all critical and major DFM findings before CDR
• Direct process engineering, tooling design, production BOM control, and work instruction development
• Lead manufacturing readiness assessment and MRR preparation — present manufacturing readiness evidence to the CTO

Automated Assembly & Test

• Design, commission, and operate robotic assembly systems; maintain automation uptime ≥95%
• Own ATE design and development — board, subsystem, and spacecraft-level automated test
• Achieve ≥95% fault detection to LRU level and ≤0.5% false failure rate
• Own Test Program Set (TPS) development, validation, and production test software

Production Line Operations

• Manage daily rate at the 5 SC/day target through factory layout optimization and workforce planning
• Maintain station utilization balance (60–90% per station) and enforce hold point compliance
• Drive headcount growth capped at 20% of volume growth rate

Manufacturing Data & Quality

• Implement and operate the MES including work order management, traveler control, and ATE data integration
• Monitor SPC, yield trending, and defect pareto analysis
• Enforce workmanship standards per IPC-A-610 Class 3; maintain dotted-line to VP, MA&Q for quality system compliance

• 15+ years of progressive manufacturing and production engineering experience; at least one program carried from factory design through full-rate production at a sustained rate of ≥100 units/week
• Direct accountability for production rate, yield, and unit cost on a high-complexity electromechanical or aerospace product at rate — low-rate experience is not a substitute
• Demonstrated experience designing, commissioning, and operating robotic assembly systems, ATE, and automated material handling
• Direct accountability for ATE design, fault coverage validation, and production test software
• Track record of embedding DFM discipline in product design teams during development — not as a production afterthought
• Hands-on MES experience including work order management, traveler control, ATE data integration, and as-built genealogy
• Demonstrated record of building multi-discipline manufacturing engineering teams including managing embedded engineers
• Bachelor's or Master's degree in Mechanical, Manufacturing, Industrial Engineering, or related field — or equivalent verifiable experience

• Experience in aerospace or defense high-rate production (satellites, missiles, avionics, or comparable complex systems)
• Direct experience with satellite manufacturing or space hardware production
• Familiarity with Design-to-Cost (DTC) methodologies and production cost modeling
• Experience with lean manufacturing transformation in a high-complexity environment
• Familiarity with digital twin and model-based manufacturing approaches