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3 days ago
A Healthcare Data Engineer is required to support AI/ML initiatives through advanced data preparation and management.
- Responsibilities include cleaning, rationalizing, normalizing, and integrating large healthcare datasets (claims, member, provider, clinical data) for readiness in AI-driven analytics and automation.
Proficiency in data cleaning, normalization, aggregation, and feature extraction are required. Knowledge of healthcare standards and coding systems (ICD-10, CPT, SNOMED, HL7, FHIR) is also essential.
- Skills include proficiency with SQL, Python, and automation frameworks for data workflows as well as experience integrating data from multiple healthcare systems and vendors.
- Knowledge of cloud-based solutions such as Amazon Web Services (AWS), Microsoft Azure's healthcare cloud, and Google Cloud Healthcare is also necessary.
- Additionally, expertise in APIs, specialized payer platforms, and enterprise integration platforms is required.
As a member of the team, you will have the opportunity to work on complex AI projects that challenge and inspire.
- The company fosters a nimble, client-focused environment, minimizing bureaucracy to enhance delivery and professional growth.
- Collaboration with AI/ML teams is encouraged, and there is a strong understanding of data governance, HIPAA compliance, and audit documentation.
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