Industrial Analytics Engineer L4
On-site
Boston, United States
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.
Job Description
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.
Key Responsibilities
- Build and maintain capacity models (target vs. forecast vs. gated capacity), incorporating cycle time, OEE, yield losses, and bottleneck analysis
- Develop labor models to optimize headcount, utilization, and labor cost (LOH) across production systems
- Create and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost-benefit analysis
- Lead COGS modeling, including labor, overhead, scrap, and process-driven cost components
- Support factory layout, site planning, and material flow decisions through data-driven insights and modeling
- Perform scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion plans
- Utilize and/or develop factory simulation models (e.g., FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system performance
- Support factory ramp-up, installation, and operational readiness through model validation and performance tracking
- Collaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Finance, Engineering) to align models with real-world constraints and business needs
- Translate complex 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 for operational visibility and executive decision-making
AI & Data Systems
- Introduce and implement AI-driven tools and platforms to enhance 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 and intelligent decision-making for capacity, throughput, and cost optimization
- Establish best practices for data quality, model standardization, and system integration across the organization
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
Source: the employer's careers page. Last checked 2026-10-30. Posted 2026-10-30.
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