Data Scientist
Job Overview
We are seeking an experienced Data Engineer with strong AI engineering expertise to design build and optimize large-scale healthcare data platforms. The ideal candidate will have hands-on experience in data pipelines orchestration frameworks EHR data integration and AI/ML model enablementdriving the transformation of healthcare data into actionable intelligence.
Key Responsibilities
- Architect build and optimize scalable ETL/ELT pipelines to process structured and unstructured healthcare data.
- Design data systems that directly support AI/ML workflows including feature engineering data versioning and real-time model serving.
- Ingest and normalize healthcare data from EHR systems (Epic Cerner etc.) with expertise in FHIR HL7 and Epic Clarity extracts ensuring HIPAA/HITRUST compliance.
- Implement and manage workflows using Airflow Prefect or similar orchestration tools.
- Collaborate with data scientists ML engineers and backend developers to deliver high-quality AI-ready datasets.
- Implement monitoring anomaly detection and automated quality checks for large-scale healthcare datasets.
Minimum Qualifications
- Bachelors degree in Computer Science Data Engineering AI/ML or related field.
- 4 years of experience in data engineering with proficiency in Python MongoDB and distributed data systems.
- Proven track record in building data pipelines for healthcare/EHR systems.
- Experience with data lakes cloud storage (Azure AWS or GCP) and scalable data architectures.
Highly Preferred Qualifications
- Expertise in AI/ML data pipelines including feature store design model input pipelines and real-time data streaming.
- Proficiency with Spark Databricks or equivalent big data tools.
- Hands-on experience with Azure Data Factory Synapse and AI/ML ecosystem tools.
- Experience with RESTful APIs and microservices for exposing healthcare/AI data assets.
- Knowledge of data quality lineage and governance frameworks (e.g. Great Expectations DataHub).
- Familiarity with vector databases embeddings and LLM integration for AI use cases
Required Skills:
Data Science AI ML
Data Scientist Job Overview We are seeking an experienced Data Engineer with strong AI engineering expertise to design build and optimize large-scale healthcare data platforms. The ideal candidate will have hands-on experience in data pipelines orchestration frameworks EHR data integration and AI/M...
Data Scientist
Job Overview
We are seeking an experienced Data Engineer with strong AI engineering expertise to design build and optimize large-scale healthcare data platforms. The ideal candidate will have hands-on experience in data pipelines orchestration frameworks EHR data integration and AI/ML model enablementdriving the transformation of healthcare data into actionable intelligence.
Key Responsibilities
- Architect build and optimize scalable ETL/ELT pipelines to process structured and unstructured healthcare data.
- Design data systems that directly support AI/ML workflows including feature engineering data versioning and real-time model serving.
- Ingest and normalize healthcare data from EHR systems (Epic Cerner etc.) with expertise in FHIR HL7 and Epic Clarity extracts ensuring HIPAA/HITRUST compliance.
- Implement and manage workflows using Airflow Prefect or similar orchestration tools.
- Collaborate with data scientists ML engineers and backend developers to deliver high-quality AI-ready datasets.
- Implement monitoring anomaly detection and automated quality checks for large-scale healthcare datasets.
Minimum Qualifications
- Bachelors degree in Computer Science Data Engineering AI/ML or related field.
- 4 years of experience in data engineering with proficiency in Python MongoDB and distributed data systems.
- Proven track record in building data pipelines for healthcare/EHR systems.
- Experience with data lakes cloud storage (Azure AWS or GCP) and scalable data architectures.
Highly Preferred Qualifications
- Expertise in AI/ML data pipelines including feature store design model input pipelines and real-time data streaming.
- Proficiency with Spark Databricks or equivalent big data tools.
- Hands-on experience with Azure Data Factory Synapse and AI/ML ecosystem tools.
- Experience with RESTful APIs and microservices for exposing healthcare/AI data assets.
- Knowledge of data quality lineage and governance frameworks (e.g. Great Expectations DataHub).
- Familiarity with vector databases embeddings and LLM integration for AI use cases
Required Skills:
Data Science AI ML
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