Remote Senior AI Data Scientist - Healthcare Impact

Geisinger; Pennsylvania; Hybrid; USD 140,000 - 180,000; Full time

Benefits offered by this job

Healthcare benefits from day one

Vision and dental coverage

Domestic partners benefits

Job summary

Geisinger is seeking a Senior Data Scientist to lead end-to-end data science initiatives in healthcare, building advanced AI models and guiding strategic analytics. You will mentor junior data scientists and collaborate with clinical and IT teams to translate complex findings into actionable insights that improve patient care and operational efficiency.

The role emphasizes deploying models to production, validating results, and staying current with the latest ML developments in healthcare.

Qualifications

• Bachelor's degree in a related field required.
• Minimum of 4 years of relevant experience required.
• Strong knowledge of ML techniques and healthcare data is essential.
• Experience with Epic Clarity, HL7, DICOM or similar enterprise data sources is a plus.
• Ability to mentor and develop junior data scientists.

Responsibilities

• Leads and manages the full lifecycle of data science projects from concept to deployment.
• Collaborates with cross-functional teams to define scope, objectives, and success metrics.
• Ensures projects align with organizational goals and deliver measurable healthcare outcomes.
• Develops and validates ML models using diverse healthcare data.
• Applies rigorous evaluation to ensure model accuracy, fairness, and reliability.
• Oversees production deployment and integration with existing systems.

Skills

Analytical Thinking

C++ Programming

Clinical Data Cleaning

Communication

Group Collaboration

Machine Learning Methods

Python

Statistical Methods

SQL

Education

Bachelor's Degree-Related Field of Study

Job description

Geisinger is seeking a Senior Data Scientist to lead end-to-end data science initiatives in healthcare, building advanced AI models and guiding strategic analytics. You will mentor junior data scientists and collaborate with clinical and IT teams to translate complex findings into actionable insights that improve patient care and operational efficiency.

The role emphasizes deploying models to production, validating results, and staying current with the latest ML developments in healthcare.