GE HealthCare is advancing the future of medical technology through intelligent systems powered by AI.

As a Sr Data Scientist within our Global Services – Service Technology team, you will lead the development of cutting-edge machine learning and generative AI solutions that enhance imaging system performance, enable predictive maintenance, and improve patient outcomes.

This role offers the opportunity to work on high-impact projects in a collaborative, agile environment, driving innovation across healthcare operations and customer-facing products.

Responsibilities

• Leading the design, development, and deployment of AI/ML models for remote diagnostics, predictive maintenance, and operational optimization.
• Analyzing large-scale machine and service datasets to uncover actionable insights and inform product improvements.
• Collaborating with cross-functional teams including engineering, product management, and MLOps to integrate AI solutions into commercial applications.
• Appling statistical, machine learning, and optimization techniques to solve complex healthcare challenges.
• Developing and operationalizing GenAI solutions, including RAG architectures and AI agents using AWS, Azure, and open-source tools.
• Ensuring scalability, reusability, and high-quality standards across AI products and pipelines.
• Communicating technical findings and strategic recommendations to stakeholders across business and technical domains.
• Mentoring junior team members and promote a culture of data-driven decision-making and continuous learning.

Required Qualifications

• M.S. or Ph.D. in Computer Science, Data Science, Engineering, or a related STEM field.
• Advanced experience in AI/ML development, with a strong portfolio of deployed models.

Desired Characteristics

Technical Expertise

• Experience in diagnostics/prognostics, system health monitoring, and reliability engineering.
• Strong foundation in applied analytics, statistical modeling, and feature engineering.
• Skilled in data cleaning, data quality assessment, and exploratory data analysis.
• Proficiency in Python and data science tools (e.g., Jupyter, Scikit-learn, TensorFlow, PyTorch).
• Experience with cloud platforms (e.g., AWS) and big data technologies (e.g., Spark).
• Hands-on experience with deep learning architectures (CNNs, RNNs, GANs).
• Familiarity with GenAI tools (e.g., AWS Bedrock) and RAG models.
• Knowledge of cloud-native AI development and deployment practices.
• Experience in healthcare or industrial AI applications.

Business Acumen

• Ability to translate business needs into technical solutions.
• Awareness of industry trends and emerging technologies.
• Skilled in assessing the impact of technology choices on business outcomes.

Leadership

• Proven ability to lead projects and mentor team members.
• Strong communication and stakeholder engagement skills.
• Demonstrated initiative and ownership in ambiguous environments.

Personal Attributes

• Results-driven with a collaborative mindset.
• Strong problem-solving and critical thinking abilities.
• Effective communicator with a passion for innovation and continuous improvement.