As an Industrial Engineering Analytics Engineer you will be responsible for;

• Developing and managing integrated industrial engineering models that connect capacity, labor, material flow, PFEP, and cost to support factory planning and operations.
• Building and maintaining capacity, labor, OEE, yield, scrap, and COGS models to drive operational efficiency and decision-making.
• Performing bottleneck analysis, scenario planning, sensitivity studies, and capacity expansion evaluations.
• Creating business cases for capital investments, including ROI, IRR, NPV, and cost-benefit analysis.
• Supporting factory layout, site planning, material flow optimization, and production strategy decisions through data-driven insights.
• Developing and utilizing factory simulation models to analyze throughput, system performance, and operational readiness.
• Collaborating with Manufacturing, Operations, Supply Chain, Finance, Engineering, MES, and Controls teams to align models with business requirements.
• Designing scalable data models, reporting frameworks, dashboards, and analytics systems to improve operational visibility.
• Implementing AI-driven tools, predictive analytics, and automated reporting solutions to enhance manufacturing performance.
• Presenting complex analytical findings and recommendations to leadership and executive stakeholders.

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, operations analysis, or a related discipline.
• Strong experience building capacity and labor models from the ground up.
• Expertise with OEE modeling, including availability, performance, and quality metrics.
• Advanced proficiency with Excel, Python, SQL, and reporting tools such as Power BI or Tableau.
• Experience developing business cases using ROI, IRR, NPV, and cost-benefit analysis methodologies.
• Knowledge of COGS modeling, manufacturing cost structures, yield analysis, and scrap reduction strategies.
• Experience with factory simulation tools such as FlexSim, AnyLogic, Simio, or similar platforms.
• Strong understanding of manufacturing systems, capacity planning, material flow, and industrial engineering principles.
• Excellent analytical, problem-solving, and executive communication skills.
• Experience translating complex data into actionable recommendations for technical and non-technical stakeholders.
• Familiarity with AI-driven analytics, predictive modeling, and continuous improvement methodologies is preferred.

Salary Range: $90K-$135K

The actual salary offered is dependent on various factors including, but not limited to, location, the candidate’s combination of job-related knowledge, qualifications, skills, education, training, and experience.