Senior Manufacturing Analytics Engineer — Industrial AI

"We energize society" by supporting our customers to make the transition to a more sustainable world, based on innovative technologies and our ability to turn ideas into reality. With nearly 100,000 employees around the world, we shape the energy systems of today and tomorrow. Senior Engineer – Manufacturing Process Analytics & Industrial AI About the Role Location United States of America Florida Orlando Company Organization EVP Global Functions Business Unit Strategic Procurement Full-time Experience Level Experienced Professional A Snapshot of Your Day As a Senior Engineer – Manufacturing Process Analytics within SCM Procurement / Supply Chain Logistics, you are part of the Siemens Energy Strategic Procurement function and Corporate SQD team, focused on driving data driven supplier capability and manufacturing excellence. You will lead the development and deployment of sensors monitoring manufacturing processes, developing manufacturing process analytics, predictive analytics models, and digital qualification standards across Siemens Energy’s global supplier base. Your work will transform how supplier capability is assessed—moving from static audits toward continuous, data driven, and predictive “digital fingerprinting” of supplier performance. You collaborate closely with Commodity Managers, Supplier Development (SQD), Engineering, Digital/IT teams, and supplier partners to: Build data-driven supplier capability frameworks Improve manufacturing performance using advanced analytics Establish digital, scalable approaches to supplier qualification and performance monitoring Your role bridges manufacturing, data science, and supply chain execution, enabling more proactive, predictive, and resilient supply chains. How You’ll Make an Impact Manufacturing Process Analytics & Predictive Insights : Develop and implement advanced analytics models (statistical, machine learning, predictive) to forecast quality risks, process instability, and supply disruptions, while analyzing supplier manufacturing data (yield, defects, throughput, cycle time) to generate actionable insights. Supplier Capability & Performance Analytics : Proactively assess supplier capabilities, identify operational gaps, and drive targeted development actions. Establish KPI frameworks, dashboards, and digital performance monitoring systems for supplier quality and manufacturing capability. Digital Qualification Standards & “Digital Fingerprint” : Define and deploy digital supplier qualification standards, integrating process capability metrics, quality system maturity, and data integrity. Develop a “digital fingerprint” of suppliers, combining historical performance data, process signatures, and risk indicators. Supplier Development & Manufacturing Engagement : Work directly with suppliers and SQD teams to enable sensor implementation for real-time monitoring, drive process improvements using data insights, and implement corrective actions based on analytics. Engage on supplier shop floors to validate insights and ensure practical implementation. Cross-Functional Analytics Leadership : Collaborate with engineering, manufacturing, and digital/IT teams to align analytics with product and process requirements. Lead cross-functional projects that deploy analytics solutions at scale, improving efficiency, cost, and quality. Continuous Improvement & Innovation : Lead root cause investigations using statistical techniques and data models, drive lean/six sigma/kaizen initiatives enabled by analytics, and identify emerging technologies in smart manufacturing, AI/ML in supply chain, and digital twin/process simulation. What You Bring Education & Experience : Bachelor’s or Master’s degree in Engineering (Manufacturing, Industrial, Mechanical, Materials, Chemical), Data Science, or related fields, with 5+ years in manufacturing/process engineering or analytics. Industrial Background : Experience in industrial environments (OEM, aerospace, energy, automotive) and proven application of data-driven approaches for performance improvement. Technical Skills : Strong expertise in statistical analysis, predictive analytics, machine learning, and familiarity with manufacturing data sources (MES, ERP, SCADA, IoT). Tools Proficiency : Proficient in programming and data analysis tools such as Python, R, SQL, and data visualization platforms like Power BI and Tableau. Analytical & Communication Skills : Strong analytical mindset with the ability to translate data into actionable insights and effectively communicate with both technical and non-technical stakeholders. Legal Authorization : Applicants must be legally authorized to work in the U.S. without employer-sponsored work authorization; Siemens Energy employees with visa sponsorship may qualify for internal transfers. About the Team You will be joining a team of technical experts in manufacturing processes, technologies and quality practices working globally to enhance the supply chain resiliency and supplier (SE and external) capability. Our Vision is to be the benchmark SQD organization for resilient, circular, and smart manufacturing supply networks. Our mission is to use qualification/supplier excellence, data analytics/AI to reduce n‑tier risk, increase capacity, maintain low NCCs, and improve circularity—while delivering on CCM(D) priorities. Rewards Career growth and development opportunities Supportive work culture and a healthy work‑life balance Flexible work environment with flex hours, telecommuting and digital workspaces Competitive total rewards package Flexible benefits and savings programs Parental leave Profit sharing Contribute to our social responsibility initiatives Equal Employment Opportunity Statement Siemens Energy and Siemens Gamesa Renewable Energy is an Equal Opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law. California Privacy Notice: California residents have the right to receive additional notices about their personal information. Click here to read more. #J-18808-Ljbffr Siemens Gas and Power GmbH & Co. KG