Industrial Analytics Engineer L4

Wipro • Boston, MA

3d

About The Position

The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to improve manufacturing efficiency, capacity planning, and cost optimization. The role includes developing capacity, labor, cost, and factory simulation models; supporting capital investment evaluations, factory layout and site planning, ramp-up, installation, and operational readiness; and providing data-driven recommendations to cross-functional teams. The engineer will also introduce AI-driven tools, design scalable data models and architecture, develop analytics standards and governance, automate data pipelines, and enable predictive analytics for capacity, throughput, and cost decisions. The role works with Manufacturing, Operations, Supply Chain, Finance, Engineering, MES, and Controls teams to align models with operational constraints, integrate shop-floor data, and deliver useful insights and dashboards.

Requirements

• 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.
• Robotics experience is listed as a mandatory skill.
• The posting separately lists 5–8 years of experience.

Responsibilities

• Build and maintain capacity models comparing target, forecast, and gated capacity, incorporating cycle time, OEE, yield losses, and bottleneck analysis.
• Develop labor models to optimize headcount, utilization, and labor cost across production systems.
• Create and evaluate capital investment business cases, including ROI, IRR, NPV, and cost-benefit analysis.
• Lead COGS modeling for labor, overhead, scrap, and process-driven cost components.
• Support factory layout, site planning, and material flow decisions using 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 to analyze throughput, bottlenecks, 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 to align models with real-world constraints and business needs.
• Translate analytical outputs into executive-level insights and recommendations.
• Collaborate with MES and Controls teams to integrate shop-floor data with industrial engineering models, improve OEE measurement, and enable scalable dashboards.
• Introduce and implement AI-driven tools and platforms for industrial engineering analytics and decision-making.
• Design and manage scalable data models and data architecture for industrial engineering, 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 and intelligent decision-making for capacity, throughput, and cost optimization.
• Establish best practices for data quality, model standardization, and system integration.

Benefits

• Medical and dental benefits options
• Disability insurance
• Paid time off, inclusive of sick leave
• Other paid and unpaid leave options

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level