Community Health Systems
Sr Director Data Science & Analytics
Community Health Systems, Franklin, Tennessee, us, 37068
Overview
Senior Director - Data Science & AI. Community Health Systems (CHS) is a leading healthcare provider operating in 47 markets across 16 states with 67 acute-care hospitals and over 1,000 other sites of care including physician practices and urgent care centers. The Senior Director of Data Science & AI will be a visionary leader responsible for driving the overarching data science strategy and execution at CHS. This executive role shapes how CHS leverages data and artificial intelligence to transform healthcare delivery, improve patient outcomes, and drive operational efficiency. You will lead and mentor a high-performing team of data scientists and AI specialists, fostering a culture of innovation and data-driven decision-making across the organization. This position involves collaborating with C-level executives and leaders across clinical, financial, and operational domains to identify high-impact opportunities for AI and ML. You will guide the end-to-end development and deployment of scalable AI/ML solutions from concept to enterprise-wide implementation, ensuring measurable value and alignment with CHS\'s strategic goals.
Responsibilities
Strategic Leadership: Develop and execute a comprehensive data science and AI strategy that aligns with the organization\'s mission to provide evidence-based, safe, and quality healthcare. Define the vision and roadmap for the Clinical Data Science (CDS) team, prioritizing initiatives that drive significant business and clinical value.
Team Leadership and Development: Build, lead, and mentor a world-class team of data scientists and AI professionals. Foster a collaborative and innovative environment that encourages continuous learning and professional growth, ensuring the team has the skills and resources to succeed.
Cross-Functional Collaboration: Partner with executive leadership across quality, safety, finance, operations, nursing, and informatics to translate complex business challenges into data science problems and solutions. Serve as the primary liaison between technical teams and business stakeholders, communicating complex technical concepts to a non-technical audience.
Solution Development and Deployment: Oversee the entire lifecycle of data science projects, from ideation and model development to deployment and performance monitoring. Focus areas include patient risk prediction, algorithmic process improvement, capacity optimization, demand forecasting, and clinical documentation improvement.
Innovation and Governance: Champion cutting-edge machine learning, deep learning, and NLP techniques to solve healthcare problems. Establish best practices for data governance, model validation, and ethical AI implementation to ensure regulatory compliance and patient privacy.
Business Impact: Drive value from data assets by delivering measurable outcomes and a significant return on investment for data science initiatives.
Qualifications
An advanced degree (Master's or PhD preferred) in a quantitative discipline such as Computer Science, Statistics, Epidemiology, or Bioinformatics; clinical training is highly preferred.
A minimum of 10 years of experience in data science or a related field, with at least 5 years in a leadership role managing data science teams. Experience in a large healthcare system is strongly preferred.
Proven track record of developing and implementing successful, large-scale data science and AI initiatives that have delivered significant business value.
Demonstrated experience in shaping data science strategy and influencing executive-level decision-making.
Expertise in a broad range of machine learning techniques (regression, classification, clustering, time series, deep learning, NLP) and their application to real-world problems.
Proficiency with Python and libraries such as pandas, numpy, scikit-learn, Keras, and TensorFlow.
Strong experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and deployment of ML/AI applications in a cloud environment.
Extensive experience with large, complex datasets, including clinical and healthcare data; proficiency in data integration from multiple sources (relational databases such as BigQuery, Postgres-SQL) and data lakes.
Excellent communication and interpersonal skills, with the ability to articulate a vision, influence stakeholders, and lead cross-functional teams.
Additional Details
Seniority level: Director
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Hospitals and Health Care
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Senior Director - Data Science & AI. Community Health Systems (CHS) is a leading healthcare provider operating in 47 markets across 16 states with 67 acute-care hospitals and over 1,000 other sites of care including physician practices and urgent care centers. The Senior Director of Data Science & AI will be a visionary leader responsible for driving the overarching data science strategy and execution at CHS. This executive role shapes how CHS leverages data and artificial intelligence to transform healthcare delivery, improve patient outcomes, and drive operational efficiency. You will lead and mentor a high-performing team of data scientists and AI specialists, fostering a culture of innovation and data-driven decision-making across the organization. This position involves collaborating with C-level executives and leaders across clinical, financial, and operational domains to identify high-impact opportunities for AI and ML. You will guide the end-to-end development and deployment of scalable AI/ML solutions from concept to enterprise-wide implementation, ensuring measurable value and alignment with CHS\'s strategic goals.
Responsibilities
Strategic Leadership: Develop and execute a comprehensive data science and AI strategy that aligns with the organization\'s mission to provide evidence-based, safe, and quality healthcare. Define the vision and roadmap for the Clinical Data Science (CDS) team, prioritizing initiatives that drive significant business and clinical value.
Team Leadership and Development: Build, lead, and mentor a world-class team of data scientists and AI professionals. Foster a collaborative and innovative environment that encourages continuous learning and professional growth, ensuring the team has the skills and resources to succeed.
Cross-Functional Collaboration: Partner with executive leadership across quality, safety, finance, operations, nursing, and informatics to translate complex business challenges into data science problems and solutions. Serve as the primary liaison between technical teams and business stakeholders, communicating complex technical concepts to a non-technical audience.
Solution Development and Deployment: Oversee the entire lifecycle of data science projects, from ideation and model development to deployment and performance monitoring. Focus areas include patient risk prediction, algorithmic process improvement, capacity optimization, demand forecasting, and clinical documentation improvement.
Innovation and Governance: Champion cutting-edge machine learning, deep learning, and NLP techniques to solve healthcare problems. Establish best practices for data governance, model validation, and ethical AI implementation to ensure regulatory compliance and patient privacy.
Business Impact: Drive value from data assets by delivering measurable outcomes and a significant return on investment for data science initiatives.
Qualifications
An advanced degree (Master's or PhD preferred) in a quantitative discipline such as Computer Science, Statistics, Epidemiology, or Bioinformatics; clinical training is highly preferred.
A minimum of 10 years of experience in data science or a related field, with at least 5 years in a leadership role managing data science teams. Experience in a large healthcare system is strongly preferred.
Proven track record of developing and implementing successful, large-scale data science and AI initiatives that have delivered significant business value.
Demonstrated experience in shaping data science strategy and influencing executive-level decision-making.
Expertise in a broad range of machine learning techniques (regression, classification, clustering, time series, deep learning, NLP) and their application to real-world problems.
Proficiency with Python and libraries such as pandas, numpy, scikit-learn, Keras, and TensorFlow.
Strong experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and deployment of ML/AI applications in a cloud environment.
Extensive experience with large, complex datasets, including clinical and healthcare data; proficiency in data integration from multiple sources (relational databases such as BigQuery, Postgres-SQL) and data lakes.
Excellent communication and interpersonal skills, with the ability to articulate a vision, influence stakeholders, and lead cross-functional teams.
Additional Details
Seniority level: Director
Employment type: Full-time
Job function: Engineering and Information Technology
Industries: Hospitals and Health Care
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