Senior Data Scientist – GenAI
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Skills you'll use
What you'll do
- The ability to design and develop ML, Gen AI, NLP, LLM Models for AI data pipelines. Model components will include data ingestion, preprocessing, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering.
- Analyze large, complex healthcare datasets including electronic health records (EHR) and claims data
- Develop statistical models for patient risk stratification, treatment optimization, population health management, and revenue cycle optimization
- Build models for clinical decision support, patient outcome prediction, care quality improvement, and revenue cycle optimization
- Create and maintain automated data pipelines for real-time analytics and reporting
- Work with healthcare data standards (HL7 FHIR, ICD-10, CPT, SNOMED CT) and ensure regulatory compliance
- Develop and deploy models in cloud environments while creating visualizations for stakeholders
- Present findings and recommendations to cross-functional teams including clinicians, product managers, and executives
Who can apply
- Bachelor's degree in data science, Statistics, Computer Science, Mathematics, or related quantitative field
- 5-7 years of hands-on experience in data science, analytics, or machine learning roles
- Knowledge of ML Ops practices deploying and operationalize AI models.
- Familiarity with cloud platforms (Azure, AWS, GCP) and containerized deployments (Docker, Kubernetes).
- Demonstrated experience working with large datasets and statistical modeling
- Proficiency in Python or R for data analysis and machine learning
- Experience with SQL and database management systems
- Knowledge of machine learning frameworks such as scikit-learn, TensorFlow, PyTorch
- Familiarity with data visualization tools such as Tableau, Power BI, matplotlib, ggplot2
- Experience with version control systems (Git) and collaborative development practices
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