About the Role
Seeking a Senior Data Scientist to design, develop, and deploy end-to-end AI/ML solutions for predictive modeling, risk stratification, behavioral analytics, and treatment pathway prediction. This role involves building advanced NLP, LLM, and RAG-based applications, as well as speech and conversational AI capabilities.
Responsibilities
- Design, develop, and deploy end-to-end AI/ML solutions for predictive modeling, risk stratification, behavioral analytics, and treatment pathway prediction.
- Build advanced NLP, LLM, and RAG-based applications, including prompt engineering, fine-tuning, and clinical AI guardrails for extracting insights from unstructured data.
- Develop speech AI and conversational AI capabilities using ASR, sentiment analysis, intent classification, Text-to-SQL, and decision-support models to improve care outcomes.
- Measure model performance through A/B testing, cohort analysis, explainability (SHAP/LIME), drift monitoring, and HIPAA-compliant governance.
- Collaborate with Data Engineering to implement feature stores, MLflow, MLOps, CI/CD pipelines, and scalable real-time/batch inference solutions.
- Mentor junior data scientists, evaluate emerging AI technologies, and drive the AI roadmap by translating advanced models into actionable healthcare solutions.
Requirements
- 7+ years of hands-on data science experience building and deploying predictive analytics, NLP, and Generative AI solutions in production, preferably within healthcare or other regulated industries.
- Proven expertise across the entire machine learning lifecycle, including feature engineering, model development, deployment, monitoring, and optimization.
- Advanced Python skills with pandas, NumPy, scikit-learn, PyTorch, and TensorFlow, along with classical ML techniques such as XGBoost, LightGBM, survival analysis, time-series forecasting, and deep learning.
- Strong experience with LLMs, RAG architectures, transformer models (BERT/GPT), Hugging Face, LangChain, vector databases, and LLM fine-tuning and evaluation.
- Hands-on expertise with NLP, speech AI, Databricks (Delta Lake, MLflow, Spark), AWS (S3, SageMaker, Bedrock, Redshift, Athena), SQL, Docker, Kubernetes, and MLOps practices.
- Demonstrated leadership through mentoring, cross-functional collaboration, and the ability to communicate complex AI/ML insights to technical and business stakeholders while driving innovation and best practices.
Skills
- Predictive Modeling
- Risk Stratification
- Behavioral Analytics
- Treatment Pathway Prediction
- NLP
- LLM
- RAG
- Prompt Engineering
- Fine-tuning
- Clinical AI Guardrails
- Speech AI
- Conversational AI
- ASR
- Sentiment Analysis
- Intent Classification
- Text-to-SQL
- Decision-support Models
- A/B Testing
- Cohort Analysis
- Explainability (SHAP/LIME)
- Drift Monitoring
- HIPAA Compliance
- Feature Stores
- MLflow
- MLOps
- CI/CD Pipelines
- Real-time Inference
- Batch Inference
- Python
- Pandas
- NumPy
- Scikit-learn
- PyTorch
- TensorFlow
- XGBoost
- LightGBM
- Survival Analysis
- Time-series Forecasting
- Deep Learning
- Transformer Models (BERT/GPT)
- Hugging Face
- LangChain
- Vector Databases
- LLM Fine-tuning
- LLM Evaluation
- Speech AI
- Databricks (Delta Lake, MLflow, Spark)
- AWS (S3, SageMaker, Bedrock, Redshift, Athena)
- SQL
- Docker
- Kubernetes
Work Type
- Full-Time
- FTE
Experience Level
- Senior
- 7+ years
