Siemens

Senior Engineer - Manufacturing Process Analytics & Industrial AI

Siemens • $100K — $130K *
Orlando, FL 32828In-Person
Manufacturing & Automotive
5 - 7 years of experience
Reposted Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in relevant engineering or data science fields.
  • 5+ years in manufacturing/process engineering or analytics.
  • Experience in industrial environments such as aerospace or energy.
  • Strong expertise in statistical analysis and predictive analytics.
  • Proficient in programming tools like Python, R, SQL, and visualization tools like Power BI or Tableau.
  • Ability to translate data insights for technical and non-technical audiences. Legal authorization to work in the U.S. without sponsorship.

Responsibilities

  • Develop and implement advanced analytics models to forecast quality risks and supply disruptions.
  • Assess supplier capabilities and establish KPI frameworks and digital monitoring systems.
  • Define and deploy digital supplier qualification standards and create a 'digital fingerprint' of suppliers.
  • Engage with suppliers to implement sensor technology for real-time performance monitoring.
  • Collaborate with cross-functional teams to align data analytics with product requirements.
  • Lead continuous improvement initiatives leveraging statistical techniques and emerging technologies.

Benefits

  • Career growth and development opportunities.
  • Supportive work culture and healthy work-life balance.
  • Flexible work environment with telecommuting options.
  • Competitive total rewards package.
  • Flexible benefits and savings programs.
  • Parental leave and profit sharing.
  • Opportunities to contribute to social responsibility initiatives.
Full Job Description
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

Jobs & Careers: [2] https://jobs.siemens-energy.com/jobs

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About Siemens

Siemens AG is a German multinational conglomerate company headquartered in Munich and the largest industrial manufacturing company in Europe with branch offices abroad. The principal divisions of the company are Industry, Energy, Healthcare, and Infrastructure & Cities, which represent the main activities of the company. The company is a prominent maker of medical diagnostics equipment and its medical health-care division, which generates about 12 percent of the company's total sales, is its second-most profitable unit, after the industrial automation division. The company is a component of the Euro Stoxx 50 stock market index. Siemens and its subsidiaries employ approximately 385,000 people worldwide and reported global revenue of around €87 billion in 2019 according to its earnings release.
Learn more about Siemens
Size
305,000 employees
Industry
Business Services
Founded
1847
NASDAQ
SIEGY
* Ladders Estimates

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