Industrial Analytics Engineer L4

The Industrial Engineering Analytics Engineer will design and apply advanced analytical models that support manufacturing efficiency, capacity planning, and cost optimization. This onsite role in Boston focuses on AI-driven industrial engineering analytics, data modeling, and shop-floor integration to enable real-time visibility and decision-making.

Key Responsibilities

• Build and maintain capacity models including target versus forecast versus gated capacity, using cycle time, OEE, yield losses, and bottleneck analysis
• Develop labor models to improve headcount planning, utilization, and labor cost (LOH) across production systems
• Create and assess business cases for capital investments, including ROI, IRR, NPV, and cost-benefit analysis
• Lead COGS modeling across labor, overhead, scrap, and process-driven cost components
• Support factory layout, site planning, and material flow decisions through data-driven insights and modeling
• Conduct scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion plans
• Use and/or develop factory simulation models (FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system performance
• Support factory ramp-up, installation, and operational readiness through model validation and performance tracking
• Partner with Manufacturing, Operations, Supply Chain, Finance, and Engineering teams to align models with operational constraints and business needs
• Translate analytical outputs into clear executive-level insights and recommendations
• Collaborate with MES and Controls teams to integrate shop-floor data with IE models, ensuring accurate OEE measurement and enabling real-time, scalable dashboards
• Introduce and implement AI-driven tools and platforms to strengthen industrial engineering analytics and decision-making
• Design and manage scalable data models and data architecture for IE capacity, labor, and cost analytics
• Develop standardized systems, frameworks, and governance for data modeling, analytics, and reporting
• Automate data collection, validation, and reporting pipelines using AI and advanced analytics tools
• Enable predictive analytics to improve capacity, throughput, and cost optimization
• Define best practices for data quality, model standardization, and system integration across the organization

Required 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

Technologies

• FlexSim
• AnyLogic
• Simio
• MES

Mandatory Skills

• Robotics

Experience

• 5-8 Years

Role Overview

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

Location and Compensation

Location: Boston, MA (onsite)

Compensation: USD 60,000 - 135,000 per year