Staff Data Scientist at GE HealthCare

, , India -

Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

0.0

Posted On

13 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Statistical Methods, AI Solutions, Data Engineering, Feature Engineering, Model Deployment, Python, AWS, Azure, TensorFlow, Keras, PyTorch, Scikit-learn, GenAI, Operational Research

Industry

Hospitals and Health Care

Description

Job Description Summary The Staff Data Scientist will work in teams addressing statistical, machine learning and data understanding problems in a commercial technology and consultancy development environment. In this role, you will contribute to the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets. Job Description Staff Data Scientist (LPB1) – Enterprise AI Role Overview GE HealthCare is accelerating its transformation through a series of strategic “Big Bets” in Commercial excellence, Logistics optimization, Inventory management, and Manufacturing innovation. The Enterprise AI team, part of the Chief Data and Analytics Office, is at the forefront of delivering robust, enterprise-grade AI and ML solutions that drive measurable business impact at scale. As a Staff Data Scientist (LPB1), you will play a key role in shaping and executing our AI strategy. You’ll collaborate across a unified, cross-functional delivery organization—partnering with experts in data engineering, ML engineering, analytics, GenAI development, and Corporate Finance—to solve complex business challenges and deliver scalable solutions. Core Responsibilities Model Development & Delivery: Design, build, and deploy AI/ML models that address business challenges in commercial operations, supply chain, manufacturing, and related domains. Project Execution: Lead and contribute to data science projects from ideation through implementation, ensuring solutions are robust, scalable, and aligned with organizational priorities. Cross-Functional Collaboration: Work closely with colleagues in data engineering, ML engineering, analytics, GenAI, and business stakeholders to deliver integrated solutions and drive project success. Technical Excellence: Apply best practices in data preparation, feature engineering, model selection, validation, and deployment. Participate in code reviews and contribute to technical documentation. Continuous Improvement: Stay current with advancements in ML, GenAI, and analytics. Proactively identify opportunities to improve existing models and processes. Business Impact: Translate complex data science concepts into actionable insights for business partners, supporting decision-making and measurable outcomes. Mentorship & Learning: Share knowledge with peers, contribute to team learning, and seek opportunities for professional growth. Experience Requirements Experience: 3+ years of direct AI/ML experience with demonstrated success building and deploying enterprise-grade solutions at scale. Relevant Expertise: Proven ability to apply advanced analytics and machine learning to solve real-world problems in areas such as forecasting, pricing, customer analytics, sales planning, computer vision, and operational optimization. Education: Bachelor’s, Master’s, or PhD in Computer Science, AI, Data Science, Applied Mathematics, or related field. Technical Skills: Proficiency in ML algorithms, GenAI frameworks, and data engineering. Experience with Python, AWS, Azure, and open-source tools (R, SQL, Spark, TensorFlow, Keras, PyTorch, Scikit-learn). MLOps & Engineering: Demonstrated ability to deploy, monitor, and maintain ML and GenAI models in production environments. Industry Knowledge: Understanding of analytics practices relevant to commercial operations, logistics, inventory management, manufacturing, and finance. Communication: Strong ability to convey complex technical concepts to non-technical stakeholders and senior executives. Interpersonal Skills: Proven success working in cross-functional, hybrid, and virtual teams. Ethics & Integrity: Commitment to ethical data science practices. Travel: Willingness to travel for business meetings as needed. Additional Information Relocation Assistance Provided: No At GE HealthCare, we see possibilities through innovation. We’re partnering with our customers to fulfill healthcare’s greatest potential through groundbreaking medical technology, intelligent devices, and care solutions. Better tools enabling better patient care. Together, we are not only building a healthier future but living our purpose to create a world where healthcare has no limits.

Responsibilities

The Staff Data Scientist will design, build, and deploy AI/ML models to address business challenges and lead data science projects from ideation through implementation. Collaboration with cross-functional teams is essential to deliver integrated solutions and drive project success.