Manufacturing Analytics Engineer: Capacity & Cost Optimizer

Pittsburgh Tomorrow

Pittsburgh (Allegheny County)

Presencial

USD 120.000 - 160.000

Jornada completa

Hace 3 días

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Descripción de la vacante

Pittsburgh Tomorrow is seeking an Industrial Engineering Analytics Engineer in Pittsburgh, PA to develop and manage models for capacity planning, labor optimization, and cost analysis. You will lead CAPEX planning, OEE tracking, and scrap reduction initiatives, collaborating with Manufacturing, Operations, and Finance to drive data-driven decisions.

The role requires expertise in Excel, Power BI, and manufacturing analytics, with a strong emphasis on production efficiency, throughput

Formación

Bachelor's degree in Industrial Engineering, Mechanical Engineering, Manufacturing Engineering, Operations Research, or related discipline.
7+ years of experience in Industrial Engineering, Manufacturing Analytics, Capacity Planning, or Operations Analysis.
Strong understanding of manufacturing systems and production operations.

Responsabilidades

Develop and maintain capacity planning models to support current and future production requirements.
Perform labor planning and workforce optimization based on production demand, takt time, and utilization targets.
Build and manage COGS models including direct labor, overhead, scrap, and manufacturing costs.
Lead CAPEX planning activities including equipment justification, investment analysis, and manufacturing expansion planning.
Develop and maintain OEE models covering Availability, Performance, and Quality metrics.
Perform scrap rate analysis, yield tracking, and cost impact assessments to identify improvement opportunities.
Conduct cycle time studies, bottleneck analysis, line balancing, and productivity improvement initiatives.
Support factory capacity expansion and operational readiness through analytical modeling and validation.
Develop manufacturing dashboards and reports using Excel, Power BI, SQL, or similar analytical tools.
Collaborate with Manufacturing, Operations, Supply Chain, Finance, and Engineering teams to support data-driven decision making.
Perform scenario analysis and sensitivity studies related to capacity, labor, throughput, and manufacturing costs.
Generate management-level reports and recommendations based on industrial engineering analysis.