Senior Staff Data Scientist

GE Healthcare GE Healthcare · Healthcare · Bengaluru, Karnātaka, India · Digital Technology / IT

Senior Staff Data Scientist role focused on architecting and implementing enterprise-grade AI/ML solutions for GE HealthCare's strategic priorities. The role involves collaborating with cross-functional teams, applying advanced analytics to business challenges like supply chain optimization and commercial strategies, and championing MLOps and engineering standards for production models. Emphasis on delivering measurable business value and thought leadership in ML and GenAI.

What you'd actually do

  1. Architect and implement AI/ML solutions that operate at scale, supporting GE HealthCare’s strategic priorities and Big Bets.
  2. Work seamlessly with colleagues in data engineering, ML engineering, analytics, GenAI, and Corporate Finance to deliver cohesive, end-to-end data science solutions.
  3. Tackle a diverse range of business challenges, from optimizing supply chains and inventory, to enhancing commercial strategies and manufacturing processes. Your work may span areas such as predictive modeling for demand and pricing, customer engagement analytics, sales performance optimization, and the application of computer vision and digital twin technologies to drive operational excellence.
  4. Champion best practices in model development, deployment, and monitoring. Promote MLOps and engineering standards for scalable, reliable solutions.
  5. Ensure data science projects deliver measurable value, such as revenue growth, operational efficiency, inventory optimization, and improved financial performance.

Skills

Required

  • Python
  • AWS
  • Azure
  • R
  • SQL
  • Spark
  • TensorFlow
  • Keras
  • PyTorch
  • Scikit-learn
  • MLOps
  • GenAI frameworks
  • data engineering
  • advanced analytics
  • machine learning algorithms
  • computer vision

Nice to have

  • semantic analysis
  • operational research
  • digital twin technologies

What the JD emphasized

  • 7+ years of direct AI/ML experience with demonstrated success building and deploying enterprise-grade solutions at scale
  • deploying, monitor, and maintain ML and GenAI models in production environments

Other signals

  • Enterprise-grade AI/ML solutions
  • Deploying models at scale
  • Driving measurable business impact