Principal Data Scientist – Healthcare & Life Sciences AI, Azure ML, Databricks

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the development of data science solutions for clinical analytics, predictive modeling, and population health applications.

• Create machine learning workflows in Azure Machine Learning, guiding the process from experimentation through to deployment and monitoring.

• Develop machine learning and lakehouse solutions in Databricks utilizing MLflow, Delta Lake, and scalable data pipelines.

• Convert clinical and business inquiries into modeling strategies, followed by validation and productionization.

• Evaluate data readiness and establish feature strategies with a focus on lineage and reproducibility.

• Establish model evaluation methodologies that encompass performance, bias, explainability, and considerations for PHI.

• Provide guidance to clinical, technical, and executive stakeholders regarding the trade-offs and risks associated with AI adoption.

• Mentor other data scientists and contribute to the development of reusable healthcare machine learning patterns and delivery accelerators.

⛳️ Requirements

• Over 10 years of experience in data science, machine learning, or healthcare analytics, preferably in a consulting or client-facing capacity.

• In-depth knowledge of healthcare data, clinical workflows, and both patient and operational data.

• Practical experience with Azure Machine Learning, including experiment tracking, model management, deployment, and monitoring.

• Strong expertise in Databricks for data engineering, MLflow, Delta Lake, and collaborative data science efforts.

• A solid grounding in predictive modeling, natural language processing (NLP), classification, regression, and experimental design.

• Experience in MLOps, including continuous integration/continuous deployment (CI/CD), version control, model registry, reproducibility, and governance.

• Knowledge of model transparency, AI risk management, and environments sensitive to PHI.

• Excellent executive communication skills with the ability to simplify technical concepts for non-technical audiences.

• The technical environment includes Azure Machine Learning, Databricks, MLflow, Delta Lake, Python, and cloud-native ML pipelines.

• Preferred certifications or training include Azure AI Engineer Associate, Azure Data Scientist Associate, Azure Solutions Architect Expert, Databricks Machine Learning Professional, Databricks Data Engineer, HIPAA, Responsible AI, or clinical analytics/governance training.

🏝️ Benefits

• Opportunity to work on cutting-edge projects in a rapidly evolving field.

• Collaborative and innovative work environment.

• Professional development and growth opportunities.

• Competitive compensation and benefits package.