Data Scientist - Manufacturing Operations

• Global Footprint & Capacity Data Analysis
• Design, build, and maintain scalable analytical frameworks and data models that enable rapid, data-driven decision making related to capacity allocation, footprint strategy, and growth planning.
• Translate complex, multi-source datasets into clear insights, scenarios, and recommendations for executive and customer-facing decision making.
• Build and maintain capacity, throughput, and utilization models across multiple product lines to identify constraints, bottlenecks, and scaling limits.
• Conduct scenario analysis, sensitivity modeling, and what-if simulations to optimize plant loading, equipment utilization, and capital investment decisions.
• Capacity Planning & Optimization
• Collaborate with Engineering, Operations, Supply Chain, and Finance to define analytical assumptions, data definitions, and decision criteria for strategic manufacturing initiatives.
• Data-Driven Decision Intelligence
• Leverage and integrate data from MES, ERP, capacity planning tools, and external sources to support strategic manufacturing analysis.
• Design and maintain cost, utilization, and capacity models that enable fast, repeatable scenario evaluation and executive decision making.
• Translate complex datasets into clear insights, visualizations, and recommendations for senior leadership and customer-facing discussions.
• Process Standardization & Scalable Analytics
• Enable scalable manufacturing strategies by embedding analytics into modular BoP approaches and digital factory initiatives.
• Support new product introductions by applying data-driven manufacturability and capacity-readiness assessments early in the design and planning process.
• Continuously improve analytical frameworks to enhance speed, accuracy, and consistency of global footprint and capacity decisions.
• Education and Certifications
• 3-5+ years of experience in data analysis, manufacturing analytics, capacity planning, or operations strategy.
• Proven experience with global manufacturing operations, footprint optimization, or capacity modeling.
• Experience building analytical frameworks, scenario models, or data-driven decision tools for executives or cross-functional teams.
• Demonstrated ability to work effectively in a cross-functional environment across a diverse, global team
• Strong proficiency in AI Agent building/modeling, SQL, Python, R, or other data analysis tools.
• Experience with ERP/MES systems, BI tools (Power BI, Tableau), and capacity planning software.
• Expertise in statistical analysis, scenario modeling, forecasting, optimization, and KPIs for manufacturing or supply chain.
• Years of Experience: 3-5

None flagged.