Description
The Cost Estimator will develop piece cost and tooling estimates for assigned commodities, requiring an extensive understanding of manufacturing cost structure and supply base capability. This role involves supporting teardowns, benchmark standard methodologies, and identifying material cost reduction opportunities. The successful candidate will actively support strategic commodity initiatives with relevant cost analyses and ensure reasonable, physicals-based, Best-In-Class assumptions for part manufacturing.
Key responsibilities include:
- Developing piece cost and tooling estimates for assigned commodities
- Supporting teardowns, benchmark standard methodologies, and identifying material cost reduction opportunities
- Actively supporting strategic commodity initiatives with relevant cost analyses
- Ensuring reasonable, physicals-based, Best-In-Class assumptions for part manufacturing
- Demonstrating strong understanding of differences between Activity Based Costing, volume-based costing, and 'Should Cost'
- Providing technical guidance and variance explanations between Activity Based Costing, suppliers' costing methodologies, and 'Should Cost' estimates
- Facilitating and participating on supplier plant visits to support benchmarking, data gathering, training, negotiations, or other activities as needed
- Providing negotiation support to Supply Chain as they engage senior supplier representatives to achieve material cost reductions
- Delivering robust cost estimates and analyses in support of Program Lifecycle, Team Value Management, Benchmarking, etc.
The ideal candidate will have a Bachelor's degree in Engineering or Finance/Business degree, with 3+ years of experience in automotive manufacturing, specifically in Electrical Distribution Systems. Advanced English skills and proficiency in data analytics and costing software (FACTON, Apriori, or Siemens) are also required. Additionally, expertise in Electrical, Metal Stamping, and Plastic Molding processes, as well as a proven track record in Agile transformation and the use of AI to improve costing efficiency, are highly desirable.