Data Analyst

Overview

MP Materials (NYSE: MP) is rebuilding American industrial capability for a new era of autonomy, robotics, and electrification. MP Materials is the only U.S. company with a fully integrated rare earth supply chain—from mining and refining to advanced metal and magnet manufacturing. Our products include both the critical materials used to make permanent magnets and the finished magnets themselves—enabling next-generation technologies in robotics, automation, aerospace, transportation, defense, and energy systems.

These materials are the foundation of physical AI—the convergence of computation, movement, and control. We hire ambitious, mission-driven people who want to tackle complex challenges and shape the future of strategic industries. Our culture is rooted in teamwork, resiliency, and integrity, with a deep commitment to operational excellence and national purpose. MP is rapidly evolving from a materials producer into a leading U.S. manufacturer—and our people are driving that transformation.

MP embraces an owner operator culture, and the Data Analyst will be empowered to develop and maintain the Company’s reporting and analytics portfolio in collaboration with the broader analytics team. This position will possess a unique view of the business and support manufacturing, engineering, finance, and other functional teams in developing and analyzing operational performance, resource allocation, and future planning. The Data Analyst will be a key member of MP Magnetics analytics team.

• Collect, clean, and integrate data from multiple disparate sources, including ERP systems, production systems, and financial platforms, for use in manufacturing analysis and reporting.
• Develop advanced reports, dashboards, and visualizations to monitor manufacturing performance, operational efficiency, and financial KPIs.
• Perform in-depth statistical and trend analysis on production, inventory, and cost data to identify opportunities for process optimization and cost reduction.
• Interpret complex datasets and present actionable insights with clear distinction between data-driven facts and business recommendations.
• Support enterprise-wide analytics initiatives, including predictive modeling and process optimization projects.
• Work with engineering teams to gather and analyze process data in the context of underlying physical parameters, helping drive fundamental understanding of process performance on a first principles basis.
• Collaborate with business stakeholders to understand analytical needs.
• Develop and maintain dashboards, weekly manager reports and recurring analysis.
• Develop statistical analysis using large disparate data sources to form new insights and support data-driven decision processes.
• Provide weekly and monthly reports and analysis for senior leaders.
• Manage aspects of the analytical architecture and collection of manufacturing data.
• Other duties as assigned.

• Bachelor’s degree in Data Analytics, Industrial Engineering, Finance, Computer Science, or related field.
• 3+ years of experience in a manufacturing environment or with manufacturing data analytics; public company experience is a plus.
• Strong understanding of manufacturing processes, operational KPIs, and cost structures.
• Proficiency in data analysis tools and techniques, including advanced SQL, Power BI, Python, KNIME or similar tools preferred.
• Ability to work with large, complex datasets from multiple sources and deliver clear, actionable insights.

• Must be highly analytical, intellectually curious and a fast learner.
• Ability to identify objectives, collect and process data, analyze and interpret results, and present conclusion and recommendations.
• Must be self-directed, highly collaborative, and able to handle a variety of responsibilities.
• Ability to work with all levels within the organization, including senior management.
• Ability to work with internal customers and external agencies for compliance and controls.
• Strong verbal and written presentation skills.
• Familiarity with, or keen interest in learning about, mining, manufacturing, and industrial processes.

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