Director, Enterprise Data Science

Community Health Systems is one of the nation’s leading healthcare providers. Developing and operating healthcare delivery systems in 39 distinct markets across 15 states, CHS is committed to helping people get well and live healthier. CHS operates 69 acute-care hospitals and more than 1,000 other sites of care, including physician practices, urgent care centers, freestanding emergency departments, occupational medicine clinics, imaging centers, cancer centers and ambulatory surgery centers.

Summary:

This role is responsible for leveraging expertise in data cleaning, transformation and feature engineering, performing advanced analytics and machine learning, and implementing programming standards to derive insights from healthcare data. As a leader on the Clinical Data Science team, this role will mediate partnerships between the data science team and business and service line leaders, act as a technical expert within specific projects and service lines, be responsible for independently developing analytical pipelines and tools, and assist with the development machine learning models and advanced statistical solutions to improve clinical, operational and financial performance across the enterprise.

Responsibilities:

• Establish and enforce coding standards (SQL), documentation rules, best practices, and version control systems (GitHub) to ensure high-quality, maintainable, and scalable code across all projects.
• Utilize cloud-based technologies, such as Google Cloud Platform (GCP), for scalable data processing and analysis.
• Provide guidance and mentorship to junior team members, fostering their professional growth and development.
• Collaborate with cross-functional teams including CHS leaders, data scientists, and software engineers to identify data-driven opportunities for enhancing clinical processes and patient care.
• Oversee the design, development, and implementation of advanced analytics and machine learning models to address complex healthcare problems. This includes selecting appropriate algorithms, ensuring model accuracy and reliability, and deploying solutions into production environments.
• Manage multiple data science projects simultaneously, ensuring they are delivered on time and within budget. This involves prioritization, resource allocation, risk management, and progress tracking.
• Direct junior team members on necessary components of a clinically relevant and accurate cloud-based feature store
• Independently perform advanced analytics of clinical data and present findings to senior members of the CHS Clinical Operations leadership.
• Collaborate with healthcare professionals and domain experts to understand clinical needs and design data-driven solutions.
• Design and conduct experiments, interpret results, and communicate findings to both technical and non-technical stakeholders

Qualifications:

• Minimum Master’s degree and 2 years of direct experience in a cloud-based healthcare or healthcare adjacent field.
• Minimum 2 years of demonstrated experience of leading and developing data science and/or analytical teams in a cloud based environment.
• Expert-level proficiency in relevant programming languages (e.g., Python, R, SQL). Experience with cloud technologies (GCP, Azure, Snowflake) is highly desirable, given the scale of hospital data.
• Mastery of data cleaning, transformation, and feature engineering techniques. Experience handling diverse data types (structured, unstructured, semi-structured) common in healthcare (e.g., EMR data, imaging data).
• Demonstrated operational expertise using cloud-based platforms such as Google Cloud Platform (GCP) for data storage, processing, and deployment.
• Proven ability to design and build interactive, user-friendly dashboards using tools like Tableau, Power BI, or similar technologies. Understanding of data storytelling and effective communication of insights through visualizations is key.
• Proven ability to design, develop, and deploy advanced analytical models and machine learning algorithms (e.g., regression, classification, clustering, deep learning, time series analysis). Experience with relevant libraries (scikit-learn, TensorFlow, PyTorch) is essential.
• Demonstrated ability to mentor, train, and lead a team of junior data scientists. This involves providing constructive feedback, fostering a collaborative environment, and promoting professional development.
• Experience managing multiple data science projects simultaneously, prioritizing tasks, meeting deadlines, and adhering to budgets. Understanding of Agile methodologies is a plus.
• Strong problem-solving skills and ability to work independently and collaboratively in a fast-paced environment.
• Excellent communication and presentation skills with the ability to translate technical concepts to non-technical audiences.

Physical Demands:
In order to successfully perform this job, with or without a reasonable accommodation, the following are outlined below:

• The Employee is required to read, review, prepare and analyze written data and figures, using a PC or similar, and should possess visual acuity.
• The Employee may be required to occasionally climb, push, stand, walk, reach, grasp, kneel, stoop, and/or perform repetitive motions.
• The Employee is not substantially exposed to adverse environmental conditions and; therefore, job functions are typically performed under conditions such as those found within general office or administrative work.