Industrial Engineering Analytics Engineer Manufacturing Systems

Job Title: Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)
Location: Pittsburgh, PA (Through March 2027), then relocation to Austin, TX
Work Arrangement: Onsite
Experience Required: 7+ Years
Employment Type: Contract
Company: Intellectt Inc.
Industry: Manufacturing / Industrial Engineering / Robotics & Automation

Job Summary

We are seeking an experienced Industrial Engineering Analytics Engineer to develop and implement advanced analytical models that improve manufacturing efficiency, capacity planning, labor optimization, and cost performance.

The ideal candidate will have strong industrial engineering fundamentals combined with hands-on experience in manufacturing analytics, capacity and labor modeling, OEE, factory simulation, and data-driven decision-making.

This role will focus on developing integrated industrial engineering models connecting production capacity, labor, material flow, PFEP, and manufacturing costs to support operational and strategic business decisions.

• Develop and maintain integrated industrial engineering models covering capacity, labor, manufacturing costs, and material flow.

• Build capacity models incorporating cycle time, OEE, yield losses, bottleneck analysis, and production forecasts.

• Develop labor models to optimize workforce planning, headcount, utilization, and labor costs.

• Create business cases for capital investments using ROI, IRR, NPV, and cost-benefit analysis.

• Lead COGS modeling, including labor, overhead, scrap, and process-related costs.

• Develop and maintain scrap, yield, and manufacturing performance models.

• Design and maintain OEE models covering Availability, Performance, and Quality.

• Support factory layout, site planning, warehouse integration, and material flow optimization.

• Perform scenario analysis and sensitivity studies for production strategies and capacity expansion.

• Utilize factory simulation tools such as FlexSim, AnyLogic, or Simio to evaluate throughput and bottlenecks.

• Support factory ramp-up, installation, and operational readiness through model validation and performance tracking.

• Collaborate with Manufacturing, Operations, Supply Chain, Finance, Engineering, MES, and Controls teams.

• Translate complex analytical results into actionable insights and executive-level recommendations.

• Implement AI-driven tools and platforms to improve industrial engineering analytics.

• Develop scalable data models and architecture for capacity, labor, and cost analytics.

• Automate data collection, validation, reporting, and analytics pipelines.

• Enable predictive analytics for capacity, throughput, and cost optimization.

• Establish standardized frameworks and governance for data quality, reporting, and model integration.

• Bachelor's degree in Industrial Engineering, Mechanical Engineering, Operations Research, or a related field.

• 7+ years of experience in industrial engineering analytics, manufacturing modeling, or operations analysis.

• Strong understanding of manufacturing systems, industrial engineering principles, and capacity planning.

• Hands-on experience building capacity and labor models from scratch.

• Strong knowledge of OEE (Availability, Performance, and Quality).

• Advanced Excel modeling and strong working knowledge of Python and SQL.

• Experience with Power BI, Tableau, or similar reporting and dashboard tools.

• Strong analytical, problem-solving, and data interpretation skills.

• Ability to communicate complex analytical findings to management and executive stakeholders.

• Experience developing integrated models covering capacity, labor, COGS, PFEP, and material flow.

• Hands-on experience with FlexSim, AnyLogic, or Simio.

• Experience with ROI, IRR, NPV, and capital investment business cases.

• Knowledge of manufacturing cost structures, scrap, yield, and labor cost modeling.

• Experience with MES and Controls systems and shop-floor data integration.

• Familiarity with AI/ML applications in manufacturing analytics.

• Knowledge of Lean Manufacturing and continuous improvement methodologies.

• Experience supporting factory ramp-up and large-scale manufacturing operations.

The initial work location will be Pittsburgh, PA, through March 2027. Candidates must be willing to relocate to Austin, TX, after March 2027.