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.

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…