Job Description Summary

This hybrid role combines advanced data science expertise (approximately 70%) with service design leadership (approximately 30%) to shape the future of MRI service solutions at GE HealthCare. The individual will apply statistical, machine learning, and advanced analytics methods to large, complex datasets while also leading service design activities that translate insights into safe, effective, and scalable service solutions for GE MRI Medical Systems.

Working within cross‑functional teams spanning engineering, product management, software, service operations, quality, and field service, this role bridges data-driven innovation with hands-on service design execution. The position is ideal for a technically strong, systems-oriented problem solver who thrives in ambiguous environments and is motivated by measurable customer and operational impact.

Job Description

Staff Data Scientist Responsibilities (≈70%)

• Lead and contribute to applied analytics, predictive, and prescriptive modeling initiatives using large, complex datasets related to service operations, system performance, and customer outcomes.
• Work with internal and external stakeholders to capture data, analytics, and business requirements and translate them into validated analytical solutions.
• Develop, verify, and validate statistical and machine learning models to address customer needs and operational opportunities.
• Perform exploratory and targeted data analyses using descriptive statistics, feature extraction, and other advanced methods.
• Partner closely with software developers, software engineers, and data engineers to translate algorithms into scalable, commercially viable products and services.
• Assess data quality, perform data cleansing, and support analytics pipeline development in collaboration with data engineering teams.
• Generate technical documentation, annotated code, reports, and other project artifacts to clearly communicate methods, assumptions, results, and business impact.
• Communicate analytical methods, findings, hypotheses, and recommendations to technical and non-technical stakeholders.

Lead Service Design Engineer Responsibilities (≈30%)

• Lead service design activities across the product lifecycle, from early concept through development, testing, and release, ensuring a customer-centered and service-ready product outcome.
• Collaborate cross-functionally with product and program management, engineering (hardware, systems, software), quality, supply chain, service operations, and field service teams to define service impact of NPI scope and translate it into actionable design transfer activities.
• Translate Field Engineer and user needs into clear, safe, and effective MR service procedures covering installation, hardware replacement, calibration, troubleshooting, and system workflows.
• Design and optimize service processes, tools, and training content to improve service delivery efficiency, effectiveness, and customer satisfaction.
• Assess documentation impacts across service manuals, training materials, and product configurations; initiate and manage changes accordingly.
• Develop, conduct, and document DIL, verification, and validation testing to identify service design challenges, resolve defects, and release high-quality service solutions.
• Leverage data analysis and performance metrics to evaluate existing service solutions and identify opportunities for improvement.
• Present service design concepts, data-driven insights, and recommendations to stakeholders, articulating technical rationale and business value.

Qualifications / Requirements

• Bachelor’s Degree in Computer Science, Engineering, Science, or another STEM discipline.
• Minimum 5 years of relevant experience (required for US-based roles).
• Strong analytical and problem-solving skills with the ability to apply data and user feedback to complex technical challenges.
• Demonstrated experience working with statistical, machine learning, or advanced analytics methods in a commercial or applied setting.
• Ability to develop timely, effective solutions in ambiguous, cross-functional environments.
• Excellent communication, presentation, and interpersonal skills, with the ability to collaborate effectively across technical and non-technical teams.

Desired Characteristics

• Master’s Degree in Computer Science, Engineering, Data Science,