
Healthcare Data Architect
3 days ago
We're seeking a Healthcare Data Engineer to support AI/ML initiatives through advanced data preparation and management.
This role involves cleaning, rationalizing, normalizing, and integrating large healthcare datasets (claims, member, provider, clinical data) to ensure readiness for AI-driven analytics and automation. You will collaborate with data scientists, engineers, and AI teams to deliver high-quality, compliant data pipelines for predictive analytics, risk stratification, fraud detection, and other use cases.
Responsibilities:
- Data Cleaning: identify and resolve errors, inconsistencies, duplicates, and missing values.
- Data Rationalization and Normalization: align with healthcare data standards and structures (ICD-10, CPT, SNOMED).
- Dataset Aggregation and Consolidation: from multiple systems (EHRs, claims, third-party vendors).
- Data Extraction Workflows: generate AI-ready features.
- Data Quality Assurance and Validation Checks: ensure reliability and accuracy.
- Collaboration with Data Scientists and AI/ML Teams: align data preparation with project goals.
- Automation and Scripting: efficient data handling.
- Maintain Thorough Documentation of Data Processes, Transformations, and Metadata.
Requirements:
- Strong Experience in Healthcare Data Engineering (Claims, EHR, Clinical Datasets).
- Proficiency in Data Cleaning, Normalization, Aggregation, and Feature Extraction.
- Knowledge of Healthcare Standards and Coding Systems (ICD-10, CPT, SNOMED, HL7, FHIR).
- Proficiency with SQL, Python, and Automation Frameworks for Data Workflows.
- Hands-on Experience Integrating Data from Multiple Healthcare Systems and Vendors.
Benefits:
- Dynamic Team Environment.
- Leadership with Big Four Consulting Experience.
- Profit-Sharing Model.
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