Clinical Data Scientist

Community Health Systems Professional Services CorporationFranklin, TN

About The Position

The Clinical Data Scientist is responsible for leveraging your expertise in data analytics, advanced statistical methods, and programming to derive insights from clinical data. As a member of the Clinical Data Science team, this role will be responsible for analyzing complex clinical datasets, developing predictive models, and translating insights into actionable recommendations for improving patient care and outcomes.

Requirements

  • Master's degree in Data Science, Computer Science, Bioinformatics, or a related field.
  • Proven experience in analyzing clinical data and implementing machine learning models.
  • Proficiency in Python programming and associated libraries.
  • 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

Responsibilities

  • Collaborate with cross-functional teams including clinical leaders, data scientists, and software engineers to identify data-driven opportunities for enhancing clinical processes and patient care.
  • Utilize cloud-based technologies, such as Google Cloud Platform (GCP), for scalable data processing and analysis.
  • Implement best practices for data management, including data quality assessment, data validation, and data governance.
  • Utilize Python programming and associated libraries such as TensorFlow, SciPy, PyTorch, Keras, Pandas and NumPY to create, train, test and implement clinically meaningful data science models.
  • Develop and implement machine learning model features, and create an maintain a clinically relevant and accurate cloud-based feature store.
  • Lead the analysis of clinical data to identify patterns, trends, and correlations relevant to healthcare outcomes.
  • Develop and implement machine learning algorithms and statistical models to predict patient outcomes, optimize clinical and operational strategies, and support clinical decision-making.
  • 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
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