Supply Chain Data Scientist – Radiopharma US & Canada

GE Healthcare GE Healthcare · Healthcare · United States · Remote · Digital Technology / IT

This role focuses on developing advanced analytics and decision-support tools for GE Healthcare's RadioPharma supply chain, aiming to improve reliability, network efficiency, and patient access. The Data Scientist will analyze operational, manufacturing, and logistics data, build models for risk identification and forecast accuracy, and collaborate with various teams to translate operational questions into data-driven insights. While machine learning is mentioned, the primary focus is on operational analytics and optimization within a healthcare supply chain context.

What you'd actually do

  1. Develop analytics that support PET supply chain reliability and On-Time Delivery (OTD) across manufacturing, quality, and logistics operations
  2. Analyze manufacturing and distribution data to identify leading indicators of supply risk or operational failure
  3. Build analytics supporting cyclotron production, synthesis operations, QC release, and radiopharmacy dispensing performance
  4. Perform deep analysis of large operational datasets to uncover patterns in manufacturing, logistics, and order behavior
  5. Apply statistical and predictive techniques to identify operational risk signals

Skills

Required

  • SQL
  • Python or R
  • Data visualization tools (Power BI, Tableau, or similar)
  • Statistical modeling and data mining techniques
  • Large dataset analysis

Nice to have

  • Supply chain analytics
  • Manufacturing analytics
  • Operations research
  • Demand forecasting
  • Optimization modeling
  • Experience supporting manufacturing or supply chain operations
  • Experience analyzing production, logistics, or distribution networks
  • Familiarity with ERP, planning, or operational data systems
  • Exposure to predictive analytics or machine learning applied to operational data

What the JD emphasized

  • 5–10+ years experience
  • Experience working with operational, manufacturing, or logistics datasets