Sr Director Data Science & Analytics

Senior Director - Data Science & AI

Community Health Systems (CHS) is one of the nation’s leading healthcare providers. Developing and operating healthcare delivery systems in 47 distinct markets across 16 states, CHS is committed to helping people get well and live healthier. With 67 acute-care hospitals and over 1,000 other sites of care—including physician practices, urgent care centers, and more—CHS is dedicated to providing comprehensive healthcare services.

Job Summary

The Senior Director of Data Science & AI will be a visionary leader responsible for driving the overarching data science strategy and execution at Community Health Systems. This executive role is pivotal in shaping how CHS leverages data and artificial intelligence to transform healthcare delivery, enhance 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 machine learning. The Senior Director will guide the end-to-end development and deployment of scalable AI/ML solutions, from initial concept to enterprise-wide implementation, ensuring they deliver measurable value and align with CHS's strategic goals.

Key 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. You will define the vision and roadmap for the Clinical Data Science (CDS) team, identifying and 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. You will serve as the key liaison between technical teams and business stakeholders, effectively 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. This includes application areas such as patient risk prediction, algorithmic process improvement, capacity optimization, demand forecasting, and clinical documentation improvement.
• Innovation and Governance: Champion the adoption of cutting-edge machine learning, deep learning, and NLP techniques to solve complex healthcare problems. You will also establish best practices for data governance, model validation, and the ethical implementation of AI to ensure regulatory compliance and patient privacy.
• Business Impact: Drive the creation of value from the organization's data assets by focusing on delivering measurable outcomes and a significant return on investment for all data science initiatives.

Qualifications

• An advanced degree (Master's or PhD preferred) in a quantitative discipline such as Computer Science, Statistics, Epidemiology, or Bioinformatics is required. Prior 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 (including regression, classification, clustering, time series modeling, deep learning, and NLP) and their application to real-world problems.
• 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.
• Excellent communication and interpersonal skills, with the ability to articulate a vision, influence stakeholders, and lead cross-functional teams.