AmeriHealth CaritasRemote
Healthcare Enterprise Analytics Data Scientist Senior
United States
Full-time
2 weeks ago
H1B Sponsor Likely
Key skills
Machine LearningData SciencePythonHealthcare Data StandardsCloud PlatformsData VisualizationStatistical AnalysisCollaborationCommunicationProblem SolvingSQLRAIMLPyTorchTensorFlowscikit-learnMLOpsXGBoostAnalyticsDatabricksSparkAzure
About this role
AmeriHealth Caritas is a mission-driven organization focused on delivering comprehensive healthcare solutions. The role of Healthcare Enterprise Analytics Data Scientist Senior involves leveraging advanced analytics, machine learning, and AI to improve healthcare delivery and member outcomes while collaborating with various teams to implement scalable solutions.
Responsibilities:
- Design, develop, and deploy machine learning and AI models to support healthcare use cases such as risk prediction, care management, disease progression, and utilization forecasting
- Perform data exploration, wrangling, and advanced statistical analysis using structured and unstructured healthcare data (e.g., claims, EMR, SDoH, labs)
- Collaborate with data engineers and MLOps teams to operate models in a scalable and maintainable environment
- Partner with clinical and business stakeholders to understand needs and translate them into technical solutions
- Evaluate model performance using appropriate metrics and ensure model fairness, transparency, and regulatory compliance
- Contribute to the design and enhancement of AI pipelines and reusable components
- Develop dashboards and data visualizations to communicate results and support decision-making
- Stay current on the latest AI/ML technologies, healthcare trends, and research, and apply them to solve emerging challenges
Requirements:
- Master's degree in Data Science, Computer Science, Statistics, Biomedical Informatics, or a related field
- At least five (5)+ years of hands-on experience in data science in a healthcare setting
- Strong knowledge of Python, R, SQL, and common ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost)
- Experience with cloud platforms (e.g., Azure) and tools like Databricks
- Understanding of healthcare data types and standards (e.g., ICD, CPT, HL7, FHIR)
- Experience working with large datasets and distributed computing frameworks (e.g., Spark)
- PhD in Data Science, Computer Science, Statistics, Biomedical Informatics, or a related field