Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)

Delta System & Software, Inc.; Pittsburgh (Allegheny County); On-site; USD 110,000 - 170,000; Full time

Job summary

Delta System & Software, Inc. in Pittsburgh, PA is seeking an Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling) to lead advanced analytical IE models across capacity, labor, material flow and costs.

You will drive data-driven decisions for factory operations and site planning using AI-driven analytics and simulation. The role requires strong IE fundamentals, experience with OEE, PFEP integration, and business case development in a large-scale manufacturing environment.

Qualifications

• Experience with greenfield or brownfield projects.
• Capacity planning expertise.
• Labor planning expertise.
• Material planning experience.
• PFMEA knowledge.
• Lean manufacturing experience.
• Six Sigma certification or experience.
• Excel proficiency.
• CAPEX management experience.
• Capital investment analysis including ROI/IRR/NPV/cost-benefit.
• Design and maintain OEE models.
• Support ramp-up, installation, and readiness via model validation.
• Layout planning experience.
• Simulation tools experience.
• AI-driven tools knowledge.

Responsibilities

• Develop and own integrated IE models including capacity, labor, material flow, PFEP and COGS.
• Build capacity models with cycle time, OEE, yield losses, bottleneck analysis.
• Develop labor models to optimize headcount, utilization and cost.
• Create and evaluate capital investment business cases using ROI/IRR/NPV.
• Lead COGS modeling including labor, overhead, scrap and process costs.
• Monitor scrap and yield models to identify cost improvements.
• Design and maintain OEE models for availability, performance and quality.
• Perform buffer and WIP analysis to optimize production flow.
• Develop PFDs and Value Stream Maps.
• Integrate PFEP data into manufacturing models.
• Support factory layout, site planning and material flow optimization.
• Run scenario analyses for production strategies and capacity expansion.
• Utilize or develop factory simulation models to evaluate throughput.
• Support ramp-up, installation and operational readiness through validation.
• Collaborate with cross-functional teams and translate outputs to exec level.

Skills

Capacity planning

Labor planning

Material planning

PFMEA

Lean Manufacturing

Six Sigma

CAPEX management

Capital investment analysis (ROI, IRR,

Education

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

7+ years of experience in Industrial Engineering Analytics, Manufacturing Modeling, or Operations Analysis

Tools

Excel

Python

SQL

Power BI

Tableau

FlexSim

AnyLogic

Simio

Job description

Job Title: Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)

Location: Pittsburgh, PA (Onsite)

Required Skills

• Greenfield or Brownfield project experience (Good to have)
• Capacity planning
• Labor planning
• Material planning
• PFMEA
• Lean Manufacturing
• Six Sigma
• Strong expertise in Excel
• CAPEX management (Good to have)
• Capital investment analysis (ROI, IRR, NPV, Cost-Benefit Analysis)
• Design and maintain OEE models
• Support factory ramp-up, installation, and operational readiness through model validation and performance tracking
• Layout planning (Good to have)
• Simulation tools experience (Not mandatory)
• Knowledge of AI-driven tools (Good to have)

Job Summary

The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning, and cost optimization.

This role is responsible for building and managing integrated Industrial Engineering (IE) models that connect capacity, labor, material flow, PFEP, and cost (COGS) to enable data-driven decision-making across factory and site operations.

The ideal candidate will combine strong industrial engineering fundamentals with advanced analytics, simulation, business case development, and AI-driven systems to support large-scale manufacturing environments.

Key Responsibilities

• Develop and own integrated IE models connecting capacity, labor, material flow, PFEP, and COGS.
• Build and maintain capacity models incorporating cycle time, OEE, yield losses, and bottleneck analysis.
• Develop labor models to optimize headcount, utilization, and labor cost (LOH).
• Create and evaluate capital investment business cases using ROI, IRR, NPV, and cost-benefit analysis.
• Lead COGS modeling, including labor, overhead, scrap, and process-driven cost components.
• Develop and monitor scrap and yield models to identify cost improvement opportunities.
• Design and maintain OEE models covering availability, performance, and quality.
• Perform buffer and WIP analysis to optimize production flow and reduce bottlenecks.
• Develop Process Flow Diagrams (PFDs) and Value Stream Maps.
• Integrate PFEP (Plan for Every Part) data into manufacturing models.
• Support factory layout, site planning, and material flow optimization.
• Perform scenario analysis and sensitivity studies for production strategies and capacity expansion.
• Utilize or develop factory simulation models (FlexSim, AnyLogic, Simio) to evaluate throughput and system performance.
• Support factory ramp-up, installation, and operational readiness through model validation and performance tracking.
• Collaborate with Manufacturing, Operations, Supply Chain, Finance, and Engineering teams.
• Translate analytical outputs into executive-level recommendations.
• Collaborate with MES and Controls teams to integrate shop-floor data with IE models for accurate OEE measurement and real-time dashboards.

AI & Data Systems

• Implement AI-driven tools to enhance industrial engineering analytics.
• Design and manage scalable data models and data architecture.
• Develop standardized frameworks and governance for analytics and reporting.
• Automate data collection, validation, and reporting pipelines.
• Enable predictive analytics for capacity, throughput, and cost optimization.
• Establish best practices for data quality, model standardization, and system integration.

Basic Qualifications

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, capacity planning, and industrial engineering principles.

Preferred Qualifications

• Experience building end-to-end IE models integrating capacity, labor, cost, PFEP, and material flow.
• Proficiency in capacity modeling, OEE analysis, cycle time studies, and line balancing.
• Hands-on experience with PFEP, material flow optimization, and warehouse integration.
• Experience with factory simulation tools such as FlexSim, AnyLogic, or Simio.
• Strong experience in business case development (ROI, IRR, NPV).
• Knowledge of COGS modeling, cost structures, and financial impact analysis.
• Experience with Excel advanced modeling, Python, SQL, Power BI, Tableau, or similar tools.
• Familiarity with AI/ML applications in manufacturing analytics.
• Familiarity with Lean Manufacturing and Continuous Improvement methodologies.
• Strong analytical and problem-solving skills.
• Ability to build scalable analytical models.
• Excellent communication and presentation skills.
• Ability to work across cross-functional teams.
• Strong attention to detail with a systems-level understanding of manufacturing operations.
• Ability to manage multiple projects in a fast-paced environment.