Manufacturing Analytics Engineer

Prolim global system; Austin (TX); On-site; USD 76,000 - 83,000; Full time

Job summary

Prolim global system in Austin, TX is seeking an Industrial Engineering Analytics Engineer to strengthen manufacturing decision-making with integrated modeling and analytics. This role focuses on capacity planning, labor and cost optimization, and bringing shop-floor data into clear dashboards, supported by scenario analysis and AI-enabled data systems.

The role emphasizes building scalable capacity and labor models, leveraging AI-enabled data systems, and collaborating across Manufacturing,

Qualifications

• Bachelor’s degree in Industrial Engineering, Mechanical Engineering, OR Operations Research or 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.
• Hands-on experience building capacity and labor models from scratch.
• Solid knowledge of OEE (Availability, Performance, and Quality).
• Advanced Excel modeling plus Python, SQL, and Power BI/Tableau.
• Strong analytical and numerical skills with ability to generate reports.
• Excellent communication, including presenting executive-level insights and recommendations.

Responsibilities

• Develop industrial engineering models connecting capacity, labor, and manufacturing costs.
• Build capacity models using cycle time, OEE, yields, bottlenecks, and production forecasts.
• Create labor models to optimize headcount, utilization, and labor costs.
• Evaluate capital investment cases using ROI, IRR, NPV, and cost-benefit analysis.
• Lead COGS modeling including labor, overhead, scrap, and process costs.
• Develop scrap and yield models to quantify cost impacts.
• Design and maintain OEE models to improve manufacturing efficiency.
• Support factory layout, site planning, and material flow decisions with data analytics.
• Run scenario analysis and sensitivity studies for production strategies and capacity expansion.
• Develop or leverage factory simulation models using FlexSim, AnyLogic, Simio.
• Support ramp-up, installation, and readiness through model validation and performance tracking.
• Collaborate with Manufacturing, Operations, Supply Chain, Finance, and Engineering.
• Translate analyses into business insights and recommendations.
• Work with MES and Controls teams to integrate shop-floor data into IE models and dashboards.

Skills

Capacity planning

Labor optimization

Data analytics

Scenario analysis

Executive-level insights

Education

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

Tools

Excel

Python

SQL

Power BI

Tableau

FlexSim

AnyLogic

Simio

MES

Job description

Prolim global system is seeking an Industrial Engineering Analytics Engineer to strengthen manufacturing decision-making with integrated modeling and analytics. This role focuses on capacity planning, labor and cost optimization, and bringing shop-floor data into clear dashboards, supported by scenario analysis and AI-enabled data systems. The position is based in Austin, TX (onsite).

What you will do

• Develop industrial engineering models that connect capacity, labor, and manufacturing costs (COGS).
• Build and maintain capacity models using cycle time, OEE, yield losses, bottleneck analysis, and production forecasts.
• Create labor models to optimize headcount, utilization, and labor costs.
• Evaluate capital investment business cases using ROI, IRR, NPV, and cost-benefit analysis.
• Lead COGS modeling, including labor, overhead, scrap, and process-related costs.
• Develop scrap and yield models to quantify cost impacts and support improvement opportunities.
• Design and maintain OEE models to improve manufacturing efficiency.
• Support factory layout, site planning, and material flow decisions using data analytics.
• Run scenario analysis and sensitivity studies for production strategies and capacity expansion.
• Develop or leverage factory simulation models using FlexSim, AnyLogic, Simio, or similar tools.
• 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 findings into business insights and recommendations.
• Work with MES and Controls teams to integrate shop-floor data into IE models and operational dashboards.

Core 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.
• Hands-on experience building capacity and labor models from scratch.
• Solid knowledge of OEE (Availability, Performance, and Quality).
• Advanced skills in Excel modeling, plus Python, SQL, and Power BI/Tableau or similar analytics tools.
• Strong analytical and numerical skills with the ability to independently generate reports.
• Excellent communication skills, including presenting executive-level insights and recommendations.

AI and data systems

• Implement AI-driven tools and platforms to improve industrial engineering analytics.
• Design scalable data models and architecture for capacity, labor, and cost analytics.
• Develop standardized frameworks for data modeling, 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.

Preferred experience

• Experience developing end-to-end industrial engineering models integrating capacity, labor, cost, PFEP, and material flow.
• Hands-on experience with PFEP, material flow optimization, and warehouse integration.
• Experience with factory simulation tools such as FlexSim, AnyLogic, or Simio.
• Strong business case development skills involving ROI, IRR, and NPV.
• Knowledge of COGS modeling, cost structures, and financial impact analysis.
• Proficiency with advanced Excel, Python, SQL, Power BI, or Tableau.
• Familiarity with AI/ML applications in manufacturing analytics.
• Knowledge of Lean Manufacturing and continuous improvement methodologies.
• Ability to build scalable models supporting both tactical and strategic decisions.

Compensation and work setup: $55.00 to $60.00 per hour. Expected hours: 40.0 per week. Work location: in person.

Technologies: Excel, Python, SQL, Power BI, Tableau, FlexSim, AnyLogic, Simio, MES.