Manufacturing Analytics Engineer: Capacity, COGS & OEE

TechDoQuest

Pittsburgh (Allegheny County)

On-site

USD 110,000 - 140,000

Full time

2 days ago

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Job summary

TechDoQuest is seeking an experienced Industrial Engineer to develop and manage models that support capacity planning, labor optimization, and cost reduction across manufacturing operations. You will build dashboards in Excel/Power BI, perform OEE analysis, CAPEX justification, and collaborate with cross-functional teams to drive data-informed decisions.

The role emphasizes manufacturing analytics, cost modeling, and continuous improvement, with a focus on scalable capacity planning and

Qualifications

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.

Responsibilities

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 (Cost of Goods Sold) 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 (Overall Equipment Effectiveness) 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.