Clinical Data Scientist

Community Health Systems is one of the nation’s leading healthcare providers. Developing and operating healthcare delivery systems in 40 distinct markets across 15 states, CHS is committed to helping people get well and live healthier. CHS operates 71 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:

The Clinical Data Science (CDS) team’s vision is to leverage data to provide evidence based, safe, quality healthcare to the communities we serve. The clinical data scientist role is established to foster value creation and implementation of the organization’s data science strategy through the use of the organization’s data assets. This role will lead and contribute to the development of predictive analytics products for various applications that are focused within Physician Practice Services’ (PPS), targeting physician practice related goals and objectives for CHS. PPS operations include a large and complex organization within CHS, with data generated from over 6 million annual patient encounters across over 900 physician practices.

Responsibilities:

• Collaborate with multiple teams of executives and leaders in areas including quality, safety, finance, operations, nursing, informatics, etc. to characterize opportunities, propose potential AI/ML infused solutions and initiatives that drive improvements.
• Lead building of end-to-end data science solutions, by employing statistical/machine learning methods to real world problems with measurable outcomes; deep knowledge of applied statistics, including machine learning algorithms, deep neural networks, NLP, recommender systems and/or anomaly detection methods.
• Drive value drawing from knowledge and experience in areas such as machine learning/AI, constrained optimization, statistical theory, graph theory and/or related fields.
• Application areas include, but are not limited to, patient return risk prediction, algorithmic process improvement, capacity optimization, demand forecasting, network flow and capture optimization, clinical documentation improvement, LLM-driven physician code generation, etc.

Qualifications:

• An advanced degree in a qualitative discipline such as Data Science, Computer Science, Engineering, Biostatistics, Epidemiology, etc. is required. Demonstrated prior experience within a healthcare setting is a preferred.
• Experience in applied Data Science or related field required.
• Experience working with large clinical databases, to clean, standardize and integrate data from multiple sources would be a strong consideration.
• Proficiency in integrating data from traditional relational databases (BqSQL/PostgreSQL/Teradata etc.) as well as other data architectures such as data lakes.
• Experience creating visualizations, reports and dashboards using BI tools such as Looker/Tableau/Data Studio.
• Experience with advanced analytics using Python, and proficiency in libraries such as matplotlib, pandas, numpy, scipy, sklearn, Keras, TensorFlow etc.
• Experience in application of advanced machine learning techniques to tasks such as regression, classification, clustering, time series modelling etc.
• Experience with cloud deployment of ML/AI applications.
• Experience facilitating large projects which includes implementation of health technology and related processes for operational success.

*Visa Sponsorship is not anticipated for this role

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.