Principal Data Automation Engineer/ Data Scientist, Supply Chain

Oracle Oracle · Enterprise · Nashville, TN +1

This Principal Data Automation Engineer role focuses on designing, developing, and implementing AI-enabled automation, predictive analytics, and operational intelligence solutions for Oracle's global supply chain. The role involves building scalable data platforms, ML models for supply chain optimization, and automation frameworks to improve efficiency and decision-making. It requires strong data engineering, ML, and automation skills, with an emphasis on applying these technologies to solve supply chain challenges.

What you'd actually do

  1. Design, build, and maintain scalable data automation solutions supporting OCI's global supply chain.
  2. Develop AI and machine learning models that improve forecasting, inventory optimization, supply planning, logistics execution, manufacturing readiness, and operational performance.
  3. Identify opportunities to eliminate manual processes through automation, predictive analytics, and intelligent workflows.
  4. Build reusable automation frameworks and data products that improve operational efficiency and business scalability.
  5. Evaluate emerging AI and automation technologies and recommend practical applications across supply chain operations.

Skills

Required

  • SQL
  • Python
  • ETL/ELT pipelines
  • data modeling
  • orchestration frameworks
  • cloud-based data platforms
  • AI/ML techniques
  • predictive analytics
  • automation frameworks
  • business intelligence and visualization tools
  • cloud technologies
  • distributed systems architectures

Nice to have

  • Oracle Fusion Cloud Applications (SCM, Procurement, Planning, ERP)
  • forecasting
  • inventory management
  • manufacturing operations
  • logistics
  • supply planning concepts

What the JD emphasized

  • Experience applying predictive analytics or machine learning to solve operational or supply chain challenges.

Other signals

  • design, develop, and implement advanced data platforms, AI-enabled automation, predictive analytics, and operational intelligence solutions
  • develop AI and machine learning models that improve forecasting, inventory optimization, supply planning, logistics execution, manufacturing readiness, and operational performance
  • identify opportunities to eliminate manual processes through automation, predictive analytics, and intelligent workflows
  • build reusable automation frameworks and data products that improve operational efficiency and business scalability
  • evaluate emerging AI and automation technologies and recommend practical applications across supply chain operations