Senior Data Scientist

Role: Senior Data Scientist

Location: Remote

Duration: Full time

We are seeking a Senior Data Scientist to develop and deploy predictive, NLP, and generative AI solutions in a healthcare environment. This role will own the full ML lifecycle from modeling and experimentation through production deployment and monitoring and partner with engineering, clinical, and business teams to turn complex data into actionable insights.

Responsibilities:

• Build and deploy predictive, risk, behavioral, and clinical models.
• Develop NLP/LLM solutions, including RAG, prompt engineering, fine-tuning, and guardrails.
• Apply speech/audio ML such as ASR, speaker diarization, sentiment, and emotion detection.
• Develop conversational AI, decision-support, Text-to-SQL, and next-best-action solutions.
• Conduct statistical analysis, A/B testing, cohort analysis, and model performance evaluation.
• Ensure model quality, explainability, bias/drift monitoring, and HIPAA compliance.
• Partner with Data Engineering on feature stores, ML pipelines, MLflow, MLOps, and CI/CD.
• Mentor junior data scientists and contribute to the AI/ML technical roadmap.

Qualifications

• 8+ years of applied Data Science experience with production ML/AI solutions.
• Master s degree in Data Science, Statistics, Computer Science, or related quantitative field; PhD a plus.
• Healthcare, managed care, or insurance experience required.
• Strong Python, SQL, pandas, NumPy, scikit-learn, and PyTorch/TensorFlow.
• Strong experience with ML algorithms including XGBoost/LightGBM, regression, survival modeling, and time-series.
• Hands-on experience with LLMs, RAG, transformers, fine-tuning, Hugging Face, LangChain, and vector databases.
• NLP/speech ML experience, including spaCy/scispaCy/MedSpaCy and ASR.
• Experience with Databricks, MLflow, Spark, AWS (S3, SageMaker, Bedrock, Redshift, Athena), Docker, and Kubernetes/EKS.
• Strong understanding of MLOps, model deployment, monitoring, and CI/CD.
• Excellent communication and collaboration skills with technical, clinical, and executive stakeholders.