Data Informatics Specialist

2 weeks ago


Williston, Florida, United States CDC Foundation Full time

About the Role

The CDC Foundation is seeking a skilled Data Scientist to play a crucial role in advancing our mission. This position will provide informatics expertise and perform health informatics activities for a public health organization, requiring specialized knowledge and skills in both health and information technology.

Responsibilities

  • Design, develop, select, test, implement, and evaluate new or modified informatics solutions, data structures, and decision-support mechanisms to support agency information management needs.
  • Create and manage systems and pipelines that enable efficient and reliable flow of data, including ingestion, processing, and storage.
  • Create new and update existing health integration engine (Rhapsody) routes to handle new data elements and formats.
  • Develop, implement, and improve data analysis and visualization tools for use by organization staff.
  • Analyze diverse datasets related to public health issues to identify trends, patterns, and correlations.
  • Apply statistical methods and machine learning algorithms to extract actionable insights.
  • Develop predictive models to anticipate disease patterns, assess risk factors, and guide intervention strategies.
  • Continuously optimize algorithms for enhanced accuracy and performance.
  • Create compelling visualizations and reports to communicate findings to partners and decision-makers.
  • Present data-driven insights in a clear and understandable manner to facilitate informed decision-making.
  • Collaborate with the public health organization and its partners to understand their data needs and objectives.
  • Provide data-driven support and guidance to inform public health policies and initiatives.

Requirements

  • Bachelor's degree in Informatics, Computer Science, Information Technology, Data Science, or a related field.
  • Minimum 5 years of relevant professional experience.
  • Proficiency in programming languages commonly used in data engineering, such as Python, Java, Scala, or SQL.
  • Knowledge of machine learning frameworks, data visualization tools, and health data types.
  • Ability to convey technical concepts to non-technical partners effectively.
  • Familiarity with API-based architectures and health data standards.


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