The business problem CHS is looking to solve is to improve healthcare outcomes, optimize operational efficiency, and generate measurable business value through data-driven innovation and artificial intelligence initiatives.
Requirements
- Expert-level knowledge of machine learning, deep learning, statistical modeling, data engineering, and model deployment best practices.
- Proficiency with advanced analytics using Python and familiarity with libraries such as pandas, numpy, scikit-learn, Keras, and TensorFlow.
- Strong experience with cloud platforms (e.g., AWS, Google Cloud, Azure, Oracle) and the deployment of ML/AI applications in a cloud environment.
- Extensive experience working with large, complex datasets, including clinical and healthcare data, and proficiency in data integration from various sources like relational databases (e.g., BigQuery, Postgres-SQL) and data lakes.
- Experience with data governance, model development, validation, deployment, monitoring, and ethical AI usage.
- Knowledge of natural language processing (NLP) and experience with predictive analytics, patient risk modeling, clinical decision support, demand forecasting, capacity optimization.
- Familiarity with regulations regarding data privacy, security, and AI model usage in healthcare (e.g., HIPAA, FDA, ONC).
Responsibilities
- Defines and leads the enterprise-wide strategy for data science and artificial intelligence, ensuring alignment with CHS’s clinical, operational, and business priorities.
- Builds, mentors, and leads a high-performing team of data scientists and AI professionals.
- Leads the end-to-end lifecycle of data science and AI initiatives - from identifying opportunities and sourcing data to model development, deployment, performance monitoring, and continuous optimization - ensuring cross-functional alignment, business adoption, and lasting impact.
- Guides the development and implementation of advanced AI use cases, including predictive analytics, patient risk modeling, clinical decision support, demand forecasting, capacity optimization, and natural language processing (NLP).
- Establishes and enforces enterprise standards for data governance, model development, validation, deployment, monitoring, and ethical AI usage.
- Champions innovation and the adoption of modern AI techniques such as deep learning, generative AI, and reinforcement learning where appropriate.
- Ensures compliance with federal and state regulations regarding data privacy, security, and AI model usage in healthcare (e.g., HIPAA, FDA, ONC).
Other
- Master's Degree in Data Science, Computer Science, Statistics, Bioinformatics, or a related quantitative field required
- Ph.D. preferred
- More than 10 years of progressive experience in data science, AI, or advanced analytics required
- 5-7 years in a leadership role managing data science teams required
- Experience in a large healthcare system preferred
