AI Data Scientist Senior

Before you apply

Job source

Himalayas

Applying on

himalayas.app

Workplace

Fully remote

US state

Nationwide remote

Category

Data Entry

Link last checked

Not checked yet

Posted

1 week ago

Closes

11/7/2026

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About the role

Location: Work from home (Pennsylvania) Shift: Days (United States of America) Scheduled Weekly Hours: 40 Worker Type: Regular Exemption Status: Yes Job Summary: The Senior Data Scientist is a strategic leader in our organization, driving the entire lifecycle of data science initiatives that directly impact healthcare outcomes. Leveraging your deep expertise and mastery of machine learning, you will spearhead the development, implementation, and evaluation of complex AI models in healthcare settings. Your ability to translate technical concepts into actionable insights will empower stakeholders to make informed decisions that enhance patient care and operational efficiency. You will also play a crucial role in mentoring and developing junior data scientists, fostering a culture of data-driven innovation. Job Duties: Leads and manages the entire lifecycle of data science projects, from conceptualization and design to development, deployment, and ongoing optimization. Collaborates with cross-functional teams to define project scope, objectives, and success metrics. Ensures projects align with organizational goals and deliver measurable impact on healthcare outcomes. Leverages deep understanding of machine learning algorithms (decision trees, neural networks, graphical models, etc.) to build sophisticated predictive models for diverse healthcare applications. Utilizes clustering, dimension reduction, and deep generative models to uncover hidden patterns and insights within large, complex healthcare datasets. Applies rigorous validation techniques to ensure model accuracy, reliability, and fairness. Oversees the deployment of models into production environments, ensuring seamless integration with existing systems. Extracts insights from clinical and operational data sources (Epic Clarity, HL7, DICOM, and other enterprise data sources) to inform decision-making and guide project direction. Translates complex technical findings into compelling narratives that resonate with non-technical stakeholders. Facilitates data-driven decision-making by effectively communicating the value and impact of AI models. Mentors and guide junior data scientists, fostering their professional growth and technical expertise. Promotes a culture of collaboration, knowledge sharing, and continuous learning within the data science team. Contributes to developing best practices and standards for data science and machine learning within the organization. Stays abreast of the latest advancements in machine learning and healthcare research to identify opportunities for improvement and innovation. Experiments with new approaches and technologies to enhance model performance and expand the organization's data science capabilities. Work is typically performed in an office environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job. *Relevant experience may be a combination of related work experience and degree obtained (Master's Degree = 2 years; PHD = 4 years ). Position Details: Education: Bachelor's Degree-Related Field of Study (Required) Experience: Minimum of 4 years-Relevant experience* (Required) Certification(s) and License(s): Skills: Analytical Thinking, C++ Programming Language, Clinical Data Cleaning, Communication, Group Collaboration, Machine Learning Methods, Python (Programming Language), Statistical Methods, Structured Query Language (SQL) OUR PURPOSE & VALUES: Everything we do is about caring for our patients, our members, our students, our Geisinger family and our communities. KINDNESS: We strive to treat everyone as we would hope to be treated ourselves. EXCELLENCE: We treasure colleagues who humbly strive for excellence. LEARNING: We share our knowledge with the best and brightest to better prepare the caregivers f

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