Data Scientist

at  GE Healthcare

JOB DESCRIPTION SUMMARY

The Staff Data Scientist will work in the Diagnostic Cardiology Algorithm Team 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 focused on computerized interpretation of ECG patterns.

EDUCATION QUALIFICATION

For roles outside USA:
Bachelor’s Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with advanced experience.
For roles in USA: Bachelor’s Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum of 6 years of experience

Desired Characteristics and Technical Expertise:

• Demonstrated skill in data management methods
• Demonstrated skill in feature extraction and realtime analytics development and deployment
• Demonstrated skill in prescriptive analytics and analytic prototyping
• Demonstrated experience with risk analysis of machine learning algorithm implementations in terms of the impact on patient safety
• Demonstrated experience developing and/or reviewing intellectual property for machine learning algorithms
• Willingness to attend scientific meetings, and customer/luminary meetings as necessary to obtain input
• Willingness to publish papers and make scientific presentations to promote Diagnostic Cardiology algorithm technology
• Demonstrated knowledge of Cardiology workflow and use of diagnostic ECG testing
• Demonstrated skill or experience with computerized analysis of physiologic signals
• Knowledge of electrocardiography and cardiac physiology

Domain Knowledge:

• Demonstrated skill in defining and delivering customer value
• Demonstrated knowledge of Cardiology workflow and use of diagnostic ECG testing
• Demonstrated skill or experience with computerized analysis of physiologic signals
• Knowledge of electrocardiography and cardiac physiology
• Experience with Quality Management Systems and Design Controls required for medical device development, including SaMD

Leadership:

• Demonstrated skill at working in a team setting
• Demonstrated skill in critical thinking and problem solving methods
• Demonstrated skill in presentation and influencing skills

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.
This role is restricted to U.S. persons (i.e., U.S. citizens, permanent residents, and other protected individuals under the Immigration and Naturalization Act, 8 U.S.C. 1324b(a)(3)) due to access to export-controlled technology. GE HealthCare will require proof of status prior to employment.

Work with customers to capture data and analytics requirements

• Develop, verify, and validate analytics to address customer needs and opportunities.
• Work alongside algorithm engineers and software engineers to translate algorithms into commercially viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Communicate methods, findings, and hypotheses with stakeholders

As a Staff 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, engineers, product managers, and end users, working in concert with partners in GE HealthCare business units. Potential application areas include ECG based diagnostics, predictive algorithms, and remote ECG monitoring across infrastructure for all patient and healthcare environments.

In this role, you will:

• Interact with global customers, clinicians, and GE HealthCare personnel to understand customer needs and clinical workflows that can be solved by AI/ML or AI/ML augmented algorithms
• Ensure scientific rigor in methods used to design, implement, and test the clinical performance of AI/ML or AI/ML augmented algorithms
• Design, implement, test and document AI/ML algorithms for Diagnostic Cardiology products based on clinical needs
• Develop strategies for organic development or external partnerships to deliver commercialize AI/ML algorithms

Work with customers to capture data and analytics requirements

• Develop, verify, and validate analytics to address customer needs and opportunities.
• Work alongside algorithm engineers and software engineers to translate algorithms into commercially viable products and services.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Work with data engineers on data quality assessment, data cleansing and data analytics
• Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
• Communicate methods, findings, and hypotheses with stakeholders.