Principal Data Scientist - (Clinical/HLS, Azure ML & Databricks)

Principal Data Scientist

Overview

Client is seeking a Principal Data Scientist with deep expertise in healthcare and life sciences, Azure Machine Learning, and Databricks. In this client-facing consulting role, you will design, develop, evaluate, and operationalize advanced analytics and AI solutions that transform clinical and operational data into scalable, governed, production-ready outcomes.

You will work across data science, clinical domains, cloud architecture, and enterprise delivery to help organizations move from experimentation to measurable business and clinical impact while ensuring solutions are secure, explainable, reproducible, and aligned with healthcare standards.

Core Responsibilities • Lead the design and delivery of data science solutions for healthcare and life sciences use cases, including clinical analytics, predictive modeling, operational intelligence, population health insights, and workflow optimization. • Design and implement machine learning workflows in Azure Machine Learning, including experimentation, model training, deployment, monitoring, evaluation, and lifecycle management. • Build and guide machine learning solutions on Databricks using notebooks, feature engineering, MLflow, Delta Lake, and scalable data pipelines. • Translate business and clinical objectives into data science solutions, develop modeling approaches, validate outcomes, and partner with engineering teams to productionize models. • Assess clinical and operational data readiness, identify data gaps, define feature strategies, and establish processes for lineage, quality validation, and model reproducibility. • Define model evaluation strategies addressing performance, bias, explainability, safety, model drift, PHI considerations, and stakeholder trust. • Serve as a trusted advisor to clinical, technical, and executive stakeholders by communicating risks, tradeoffs, value drivers, and adoption strategies for AI and machine learning solutions. • Mentor data scientists and engineers while contributing reusable healthcare ML patterns, Databricks accelerators, Azure ML templates, and delivery best practices.

Essential Qualifications, Skills, and Technologies • 10+ years of experience in data science, machine learning, healthcare analytics, AI solution delivery, or enterprise data platforms, preferably in a consulting or client-facing environment. • Strong understanding of healthcare data, clinical workflows, operational healthcare analytics, provider environments, patient data, or life sciences use cases. • Hands-on expertise with Azure Machine Learning, including experiment tracking, model management, deployment, monitoring, and integration with Azure services. • Strong experience with Databricks for data engineering, analytics, feature development, MLflow, Delta Lake, and collaborative data science workflows. • Deep knowledge of predictive modeling, NLP, classification, regression, clustering, feature engineering, experiment design, and model validation. • Experience operationalizing machine learning models using CI/CD, version control, model registry, reproducibility, monitoring, and governance practices. • Familiarity with responsible AI principles, model transparency, AI risk management, PHI-sensitive environments, auditability, and healthcare governance requirements. • Strong executive communication and stakeholder management skills with the ability to translate complex technical concepts into business-focused recommendations.

Preferred Skills or Experience • Microsoft certifications such as Azure AI Engineer Associate, Azure Data Scientist Associate, Azure Solutions Architect Expert, or related Azure AI and data certifications. • Databricks certifications including Databricks Machine Learning Professional, Databricks Data Engineer, or other Lakehouse-related credentials. • HIPAA, Responsible AI, clinical analytics, or AI governance training.

Work Details • Remote • Right to Hire position.