Job Description Summary
GE HealthCare’s Chief Data and Analytics Office team delivers innovative data, insights and AI solutions for the organization. Our Enterprise AI team works on a diverse portfolio of Machine Learning (ML), AI and GenAI projects, by combining agile and entrepreneurial drive with industry-leading methods and tools.As the Senior Data Scientist, you will be at the forefront of developing and delivering innovative algorithms that generate actionable business insights for key areas within GE HealthCare, including Finance, Commercial, Supply Chain, Quality, Operational Excellence and Lean, and Manufacturing. We are seeking a highly skilled and motivated Data Scientist with experience in AI applications to join our dynamic team.
Job Description
Core Responsibilities
Develop and implement advanced AI algorithms and models to solve complex problems across finance, manufacturing, quality, supply chain, sales & marketing.
Develop and implement advanced forecasting methodologies using technologies like batch forecasting, deep learning, simulation, and reinforcement learning to enhance decision-making.
Apply computer vision methods to drive manufacturing efficiencies and improve product quality across the GE Healthcare manufacturing network.
Collaborate with cross-functional teams to integrate AI solutions into various applications and products.
Analyze large datasets to extract meaningful insights and improve model performance.
Design and conduct digital experiments to validate and optimize AI models.
Present findings and recommendations to stakeholders in a clear and concise manner.
Collaborate with the MLOps team during AI model development, deployment and monitoring.
Proactively identify new opportunities to further leverage data science solutions – prioritizing opportunities with the biggest potential benefit to the business.
Ensure best practice adoption within the Enterprise AI team, applying appropriate levels of technical capability, standardization, and subject matter expertise.
Drive a culture of analytics and fact-based decision making through the utilization of standard methodologies and approaches.
Experience Requirements
M.S. or Ph.D. in Computer Science, Data Science, Engineering or a STEM related field with hands-on experience in developing and deploying AI models and applications.
Proficiency in the latest Python, AWS, Azure, and open-source data science tools such as Jupyter, R, SQL, Hadoop, Spark, TensorFlow, Keras, PyTorch, and Scikit-learn.
Proficiency in AI agentic development tools such as AWS Bedrock, Azure AI Foundry, Microsoft Copliot Studio and LangChain/LangGraph.
Knowledge of RAG architecture, including retrieval mechanisms and generative models.
Knowledge of deep learning architectures including CNNs, RNNs, and GANs.
Experience building RAG models and AI agents via AWS or Azure AI services.
Ability to work with large-scale datasets and perform efficient data analysis.
Expertise in transformers, self-supervised learning, and generative AI models.
Strong problem-solving skills and the ability to think critically and creatively.
Excellent communication skills and the ability to work collaboratively in a team environment.
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Additional Information
Relocation Assistance Provided: No
