Aerospace Manufacturing Ops Research Engineer

Chipton-Ross; San Antonio (TX); On-site; USD 70,000 - 100,000; Full time

Job summary

Chipton-Ross in San Antonio, TX is seeking a hands-on Industrial/Production Engineer with a focus on project planning and scheduling for an Executive Fleet program. The role requires interpreting engineering drawings, applying lean methods, and delivering data-driven improvements onsite for a 12+ month contract.

Ideal candidates have 2–5 years in scheduling and industrial engineering, with proficiency in Python, SAS, VBA, and SQL.

Qualifications

• 2–5 years in project planning/scheduling/project management.
• 2–5 years as an Industrial or Production Engineer within a factory environment.
• Fluency with Python, SAS, VBA, SQL.

Responsibilities

• Transform production intent into executable plans—design precedence networks linked to milestones and adjust them as reality changes.
• Build weekly/biweekly operating and recovery plans using constraint-based scheduling and crew cycling to protect the critical path.
• Run capacity and constraint analyses; lead process effectiveness studies that remove waste and elevate throughput.
• Deliver monthly support to barge activities: schedule development/analysis, OPE deep dives, data analytics, alternate job routing, critical-chain visibility, and chit board updates.
• Apply models, simulations, and statistical methods to optimize flow and resource utilization across facilities, personnel, materials, and equipment.
• Plan work, analyze historical trends and production impacts, and recommend staffing and process improvements across a multi-functional team.

Skills

Python

SAS

VBA

SQL

Education

BS in Industrial Engineering or ABET-accredited STEM

Tools

Aurora

IVT/Redars

Job description

Chipton-Ross in San Antonio, TX is seeking a hands-on Industrial/Production Engineer with a focus on project planning and scheduling for an Executive Fleet program. The role requires interpreting engineering drawings, applying lean methods, and delivering data-driven improvements onsite for a 12+ month contract.

Ideal candidates have 2–5 years in scheduling and industrial engineering, with proficiency in Python, SAS, VBA, and SQL.