Senior Analytics Engineer

Job description

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 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 that connect capacity, labor, material flow, PFEP, and cost (COGS) to support factory planning and operations • 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 • Develop and track scrap and yield models, quantifying cost impact and identifying improvement opportunities • Design and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improvement • Perform buffer and WIP analysis to optimize inline and interline storage, reduce bottlenecks, and stabilize production flow • Develop process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficiencies • Integrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strategies • 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, PFEP, 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 Skill Requirements Key Skills & Competencies • Strong analytical and problem-solving skills with a data-driven mindset • Ability to build scalable models and analytics systems that support both tactical and strategic decisions • Strong communication skills to translate complex data into actionable insights • Ability to work across cross-functional teams and influence decision-making • Attention to detail with a systems-level understanding of manufacturing operations • Ability to manage multiple projects and priorities in a fast-paced environment 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 Other Requirements 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 (e.g., FlexSim, AnyLogic, Simio) • Strong experience in business case development (ROI, IRR, NPV) • Knowledge of COGS modeling, cost structures, and financial impact analysis • Experience with data analysis tools (Excel advanced modeling, Python, SQL, Power BI/Tableau, or similar) • Familiarity with AI/ML applications in manufacturing analytics (preferred) • Familiarity with lean manufacturing and continuous improvement methodologies Maximum Salary (US): Minimum Salary (US): Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 223,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending June 2026 totaled $14.8 billion. Compensation and Benefits A candidate’s pay within the range will depend on their skills, experience, education, and other factors permitted by law. This role may also be eligible for performance-based bonuses subject to company policies. In addition, this role is eligible for the following benefits subject to company policies: medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance; employee assistance program; 401(k) retirement plan; 10 days of paid time off per year (some positions are eligible for need-based leave with no designated number of leave days per year); and 10 paid holidays per year. Disclaimer Privacy Statement Terms of use Sitemap Raise a Grievance We use cookies on our site. Please read more about cookies policy here. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Opens in a new tab. Copyright © 2026 HCL Technologies Limited Cookie Consent Manager When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. Because we respect your right to privacy, you can choose not to allow some types of cookies. 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