Role Description In search of a Physician, Radiologist to join our gifted team. This position is fully remote and Monday through Friday. Responsibilities include reviewing and diagnosing patients with diagnostic Imaging. Works collaboratively with Radiology Department staff and referring physicians from various areas. - Interprets imaging from various modalities using health system PACS system and voice dictation software. - Calls critical results to referring provider. - Recommends follow up imaging in accordance with PA Act 112. - Other duties as assigned. Qualifications - Doctor of Medicine (MD) or Doctor of Osteopathic Medicine (DO) degree. - Body fellowship or ability to read body imaging. - Strong leadership ability, good organizational skills, independent and critical thinking skills, sound judgment, and knowledge of legal aspects and liability of nursing practice. - Strong ability to communicate complex and/or controversial topics and concepts to a wide and diverse audience. Requirements - 2-4 years’ experience in neurology (preferred). - Experience in Healthcare setting (preferred). - Current medical license in the state of Pennsylvania. - Certification by the American Board of Radiology. - DEA License. - Act 33 with renewal. - Act 34 with renewal. - Act 73 FBI Clearance with renewal. Benefits - Excellent compensation. - Benefits. - Work-life balance. Company Description A stellar, high-quality medical team made up of leading-edge professionals is one of the factors that sets Independence Health System (IHS) apart.

• Own high-quality recruiting end-to-end, not coordinate it. • Build pipelines before you need them. • Design structured hiring processes with rigorous assessments. • Build and maintain high talent density. • Source and manage a PEO or EOR to handle employment contracts, salary administration, and benefits across multiple jurisdictions. • Design onboarding that sets people up for success. • Use data to drive people decisions. • Champion the strategic use of data, technology, and AI to strengthen people processes and outcomes.

• Help shape the systems that power how AI agents are created, connected to data, and safely deployed across the company • Create the underlying infrastructure and patterns that allow teams across Dave to build and trust AI-driven workflows • Partner closely with Data Engineering, building on a trusted data platform to create an AI Agent Factory that scales across the business • Establish how AI operates across Dave, enabling teams to move faster with better information • Build and operate systems end-to-end, focusing on execution and reliability

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets. • Design and evolve information and semantic models that make enterprise data AI-ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM-based experiences (e.g., search, retrieval-augmented generation, and copilots). • Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation). • Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns. • Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross-domain dependencies to establish trusted, reusable business meaning. • Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross-domain interoperability and AI consumption. • Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI-enabled workflows, ensuring alignment with governance standards and risk expectations. • Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms. • Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes. • Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.