Roles and Responsibilities
As a Sr Data Scientist, you will be part of a data science or cross-disciplinary team on commercially-facing development projects, typically involving large, complex data sets. These teams typically include statisticians, computer scientists, software developers, ML and MLOps engineers, product managers, and end users, working in concert with partners in GE Healthcare business units. Potential application areas include remote monitoring, diagnostics and predictive maintenance across infrastructure and industrial sectors, and operations optimization.
In this role, you will:
Analyze large datasets to extract meaningful insights and develop analytics to address customer needs and opportunities.
Perform exploratory and targeted data analyses using descriptive statistics and other methods.
Design and conduct digital experiments to validate and optimize AI models.
Work with data engineers on data quality assessment, data cleansing and data analytics
Collaborate with cross-functional teams to integrate AI solutions into various applications and products.
Collaborate with the MLOps team during AI model development, deployment, and monitoring.
Present findings and recommendations to stakeholders in a clear and concise manner.
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 Global Service Insights & Actions 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.
Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
Experience and 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.
Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets
Experience with deep learning architectures including CNNs, RNNs, and GANs.
Ability to work with large-scale datasets and perform efficient data analysis.
Expertise in transformers, self-supervised learning, and generative AI models.
Experience 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.
Experience building RAG models and AI agents via AWS or Azure AI services.
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.
Personal Attributes
Demonstrated awareness of how to succeed in ambiguous circumstances
Note
Note:
To comply with US immigration and other legal requirements, it is necessary to specify the minimum number of years' experience required for any role based within the USA. For roles outside of the USA, to ensure compliance with applicable legislation, the JDs should focus on the substantive level of experience required for the role and a minimum number of years should NOT be used.
This Job Description is intended to provide a high level guide to the role. However, it is not intended to amend or otherwise restrict/expand the duties required from each individual employee as set out in their respective employment contract and/or as otherwise agreed between an employee and their manager.
Relocation Assistance Provided: No
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