> Markdown version of [/jobs/ext/4541736-industrial-engineering-analyst](https://www.wearedevelopers.com/jobs/ext/4541736-industrial-engineering-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Industrial Engineering Analyst - **Company:** Actalent - **Location:** Austin, TX, United States - **Experience:** Expert - **Salary:** $145,600.0 - $166,400.0 - **Contract:** Temporary contract - **Skills:** Microsoft Excel, Adaptable Database Systems, Artificial Intelligence, Business Analytics Applications, Data Analysis, Data Architecture, Data Systems, Decision Support Systems, Python (Programming Language), Machine Learning, Process Driven Development, Power BI, SQL Databases, Systems Integration, Tableau (Software), Model Validation, AnyLogic, FlexSim - **Published:** November 3, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/tx/austin/52c97adb-11b3-4abe-b715-d46b7f0e7e19 ## About the Role Equities AnyLogic Dashboard Visionary Operations Leadership Automation Governance Innovation Warehousing Scalability Investments Forecasting Supply Chain Data Quality Communication Data Modeling Business Case Site Planning Microsoft Excel Problem Solving Decision Making Data Collection Cost Structures Model Validation Data Architecture Capacity Planning Scenario Analysis Lean Manufacturing Influencing Skills Advanced Analytics Scalability Design Operations Research Data Analysis Tools Cycle Time Variation Predictive Analytics Mechanical Engineering Operational Efficiency Industrial Engineering Manufacturing Operations Material Flow Management Applied Machine Learning Ability To Meet Deadlines SQL (Programming Language) Engineering Design Process Process Driven Development Data-Driven Decision Making Python (Programming Language) Continuous Improvement Process Cost Of Goods Sold (Inventory) Overall Equipment Effectiveness Manufacturing Execution System (MES) Tableau (Business Intelligence Software) At least 7 years, * Bachelors 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. * Solid understanding of manufacturing systems, capacity planning, and industrial engineering principles. * Proven experience building end-to-end industrial engineering models integrating capacity, labor, cost, and material flow. * Hands-on experience with material flow optimization and warehouse integration. * Experience with factory simulation tools such as FlexSim, AnyLogic, or comparable platforms. * Demonstrated experience in business case development, including ROI, IRR, and NPV analysis. * Knowledge of COGS modeling, cost structures, and financial impact analysis. * Advanced proficiency in data analysis tools, including Excel (advanced modeling), Python, SQL, and Power BI/Tableau or similar reporting and dashboard tools. * Strong analytical and problem-solving skills with a data-driven mindset. * Ability to translate complex analysis into clear, executive-level insights and recommendations. * Ability to work effectively across cross-functional teams and influence decision-making. * Attention to detail combined with a systems-level understanding of manufacturing operations. * Ability to manage multiple projects and priorities in a dynamic, fast-paced environment. Additional Skills & Qualifications * Familiarity with AI and machine learning applications in manufacturing analytics. * Experience introducing and implementing AI-driven tools and platforms to enhance industrial engineering analytics. * Experience designing scalable data models and data architecture for capacity, labor, and cost analytics. * Background in developing standardized frameworks and governance for data modeling, analytics, and reporting. * Experience automating data collection, validation, and reporting pipelines using advanced analytics tools. * Familiarity with lean manufacturing and continuous improvement methodologies. * Strong communication skills to translate complex data into actionable insights for technical and non-technical stakeholders. * Ability to build scalable models and analytics systems that support both tactical and strategic decisions., Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors. ## Description The Industrial Engineering Analytics Engineer leads the development and application of advanced analytical models to improve manufacturing efficiency, capacity planning, and cost optimization in large-scale production environments. This role builds and manages integrated industrial engineering models that connect capacity, labor, material flow, and cost of goods sold to enable data-driven decision-making across factory and site operations. The position combines strong industrial engineering fundamentals with advanced analytics, simulation, business case development, and AI-driven systems to support both tactical and strategic manufacturing decisions., * Develop and own integrated industrial engineering models that connect capacity, labor, material flow, and cost of goods sold to support factory planning and operations. * Build and maintain capacity models that compare target, forecast, and gated capacity, incorporating cycle time, overall equipment effectiveness (OEE), yield losses, and bottleneck analysis. * Develop labor models to optimize headcount, utilization, and labor cost across production systems. * Create and evaluate business cases for capital investments, including ROI, IRR, NPV, and detailed cost-benefit analysis. * Lead cost of goods sold (COGS) modeling, including labor, overhead, scrap, and process-driven cost components. * Develop and track scrap and yield models, quantify cost impact, and identify opportunities for improvement. * Design and maintain OEE models that capture availability, performance, and quality to drive operational efficiency and continuous improvement. * 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 develop factory simulation models (such as FlexSim, AnyLogic, and similar tools) to analyze throughput, bottlenecks, and overall system performance. * Support factory ramp-up, equipment 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 complex analytical outputs into clear, executive-level insights and recommendations for senior stakeholders. * Work closely with MES and controls teams to integrate shop-floor data with industrial engineering models, ensuring accurate OEE measurement and enabling real-time, scalable dashboards for operational visibility and executive decision-making. * 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 industrial engineering, capacity, labor, and cost analytics. * Develop standardized systems, frameworks, and governance for data modeling, analytics, and reporting across the organization. * 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. * Build scalable models and analytics systems that support both tactical and strategic manufacturing decisions. * Manage multiple projects and priorities in a fast-paced environment while meeting deadlines and quality standards.