Data Scientist AWS & Google Cloud Platform | Healthcare Industry | Local to Atlanta Position Available In Fulton, Georgia

Data Scientist AWS & Google Cloud Platform | Healthcare Industry | Local to Atlanta
Data Scientist AWS & Google Cloud Platform | Healthcare Industry

Job Location:

Atlanta, GA

Duration:

Long Term

Job Type:

W2 / Full time

Interview Mode:

2 Rounds (Tech Screening)
Local to Atlanta

Job Description:

We are seeking a Data Scientist experienced with both AWS and Google Cloud Platform to support AI/ML development in the Healthcare sector. This role will focus on enabling intelligent health systems using data-driven and cloud-native ML solutions, while ensuring scalability, security, and compliance.

Key Responsibilities:

Develop and operationalize ML models for healthcare use cases including readmission prediction, diagnostics support, claims processing, and medical NLP.
Utilize AWS SageMaker, HealthLake, Comprehend Medical, as well as Google Cloud Platform Vertex AI and Healthcare NLP APIs.
Ensure HIPAA-compliant ML architecture and data pipelines leveraging services like AWS Glue, Google Cloud Platform Dataflow, and BigQuery.
Design and deploy Generative AI/LLM applications for summarizing patient records, chatbot assistance, and literature review.
Implement MLOps pipelines for versioning, testing, and CI/CD using AWS CodePipeline or Google Cloud Platform Cloud Build.
Collaborate with clinical, data governance, and analytics teams to align ML outputs with healthcare objectives.
Use visualization tools like Looker, QuickSight, or custom dashboards to present findings to stakeholders.

Required Skills:

4 7 years of ML engineering experience, including working in cloud-native environments.
Hands-on with AWS ML and Google Cloud Platform AI platforms (SageMaker, HealthLake, Vertex AI, BigQuery, Comprehend Medical).
Experience with healthcare datasets (EHR, claims, clinical notes) and regulatory compliance (HIPAA).
Strong programming in Python, with experience in ML frameworks such as TensorFlow and PyTorch.
Demonstrated capability in building, tuning, and deploying LLM or NLP-based models in healthcare workflows.
Strong communication and ability to collaborate cross-functionally with non-technical stakeholders.

Preferred Experience:

Knowledge of

HL7, FHIR, SNOMED

CT, or other healthcare interoperability standards.
Exposure to population health analytics, digital health platforms, or patient engagement tools.
AWS or Google Cloud Platform professional certifications in ML, AI, or data engineering.

Note:

This opportunity is with ITTStar. If interested or if you know someone who is a good fit, please apply or refer.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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Dice Id:

10501611

Position Id:

8677142