Senior Industrial Engineer
On-siteGandhinagar, Gujarat, India
Job Summary
Lead development of cross-site capacity models, utilization analyses, and expansion planning studies to maximize factory output. Drive cycle time reduction and WIP optimization initiatives through Factory Physics methodologies, bottleneck analysis, and constraint management. Develop and maintain advanced analytical tools supporting factory scheduling, output optimization, and operational decision making while performing operations research to identify productivity improvement opportunities. Design predictive models, optimization algorithms, and AI-enabled analytical solutions for manufacturing applications, then lead validation of scheduling logic and manufacturing data structures. Establish standard methodologies and best practices across multiple sites, mentor junior engineers, and partner with site leadership and cross-functional teams to drive strategic improvement initiatives. Present recommendations and business cases to senior leadership to support long-range capacity plans and fab expansion scenarios.
Required Qualifications
- Bachelor's Degree in Industrial Engineering, Operations Research, Manufacturing Engineering, Systems Engineering, or related engineering discipline
- Proficiency in SQL, Python, Power BI, and statistical analysis tools
- 3–8 years of Industrial Engineering experience in semiconductor manufacturing or other complex manufacturing environments
- Experience building capacity models, productivity analyses, factory scheduling models, or optimization tools
- Demonstrated success leading cross-functional improvement initiatives
- Strong analytical, communication, and project leadership skills
- Required Travel: Yes, 10% of the time
- Shift Type: 1st Shift/Days
Desired Qualifications
- Master's Degree in Industrial Engineering, Operations Research, Data Science, Analytics, or related field
- Semiconductor wafer fabrication experience
- Experience with Factory Physics, cycle time engineering, capacity planning, production scheduling, or manufacturing optimization
- Experience with simulation, optimization modeling, machine learning, or operations research techniques
- Experience working with globally distributed teams
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