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GE Healthcare

Sr Data Scientist

Reposted 2 Days Ago
In-Office or Remote
2 Locations
Senior level
In-Office or Remote
2 Locations
Senior level
Lead the development of AI and machine learning solutions for healthcare applications, focusing on remote diagnostics, predictive maintenance, and operational optimization. Collaborate with cross-functional teams to integrate solutions and mentor junior members.
The summary above was generated by AI
Job Description SummaryGE 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.

Job Description

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.

#LI-MT1

#LI-Hybrid

Additional Information

Relocation Assistance Provided: No

Top Skills

AWS
Azure
Jupyter
Python
PyTorch
Scikit-Learn
Spark
TensorFlow

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