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 70 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 analytics, machine learning, natural language processing, advanced statistical methods, and programming to derive insights from health system data. As a member of the Data Science team, this role will be the technical expert within specific projects and service lines, responsible for independently developing machine learning models and advanced statistical solutions to improve operational, financial and health-related outcomes.

Responsibilities:

• Collaborate with cross-functional teams including operational and financial leaders, data scientists, and software engineers to identify data-driven opportunities for enhancing processes and delivery of services.
• Utilize cloud-based technologies, such as Google Cloud Platform (GCP), for scalable data processing and analysis.
• Utilize Python programming and associated libraries such as TensorFlow, SciPy, PyTorch, Keras, Pandas and NumPY to create, train, test and implement traditional data science models.
• Utilize Natural Language Processing (NLP) programming models such as BERT, NLTK, spaCy and large language models to develop bidirectional text-based models to improve clinical, financial, and operational processes that are documentation-focused.
• Direct junior team members on necessary components of a relevant and accurate cloud-based feature store
• Independently perform advanced analytics and present findings to senior members of the CHS Operations leadership.
• Independently assess and select best model-data fit, and develop and implement machine learning models to predict high value clinical, financial, and operational outcomes to support day-to-day operations across multiple services across the organization.
• Collaborate with healthcare professionals and domain experts to understand operational 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 in Data Science, Computer Science, Bioinformatics, or a related field
• Minimum 2 years of direct experience in a cloud-based healthcare or health-adjacent data environment with lead model developer experience.
• Minimum 2 years of demonstrated experience of developing, operationalizing and deploying automated data models (statistical, machine learning or artificial intelligence) in a cloud based environment.
• Advanced knowledge of cloud computing, containerization technologies like Docker and Kubernetes, and experience deploying ML models to production environments.
• Proven experience in analyzing clinical data and implementing machine learning models such as Support Vector Machines, K nearest neighbors, random forests, gradient boosed decision trees, and naïve bayes.
• Proficiency in Python programming and associated libraries for supervised machine learning including Scikit-learn, Keras, Pandas, NumPy, PyTorch, TensorFlow and Seaborn.
• Demonstrated proficiency in the development and implementation of NLP-specific applications, include tools such as sci-spacy, BERT, NLTK, or Gemini.
• Demonstrated proficiency in analyzing clinical data and implementing machine learning models such as Support Vector Machines, K nearest neighbors, random forests, gradient boosted decision trees, and naïve bayes.
• Experience with cloud-based platforms such as Google Cloud Platform (GCP) for data storage, processing, and deployment.
• 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.