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**Location: Atlanta, GA***

***THIS POSITION IS NOT REMOTE***

***U.S. Citizenship required**

****This job will close when we have received 50 applications which may be sooner than the closing date. ***

WHAT YOU'LL BE DOING DAY TO DAY

As a Data Scientist, you will use your knowledge of and experience with Centers for Disease Control and Prevention to optimize business results and customer experience by:

  • Plan and execute advanced data science projects applying statistical, machine learning, artificial intelligence, data mining, and geospatial analysis methods to public health surveillance, research, administrative, and nontraditional data sources.
  • Acquire, assess, and manage complex spatial and epidemiologic datasets, including evaluation of data quality, standards, bias, limitations, and scientific validity.
  • Develop and maintain geospatial datasets, maps, dashboards, visualizations, and analytical products to identify geographic trends, population health patterns, emerging threats, resource gaps, and areas of elevated risk.

Basic Requirements:

A. Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.

Or

B. Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience

Minimum Qualifications:

You must have one year specialized experience to perform successfully the duties of the position. To be creditable, specialized experience must have been equivalent to at least the GS-12 grade level in the Federal service performing ALL of the following:

  • Conducting complex data science analyses using statistical, machine learning, predictive modeling, data mining, artificial intelligence, or spatial modeling methods to transform large structured or unstructured datasets into actionable findings for leadership;
  • Developing geospatial data products, including geographic information system (GIS) datasets, geocoding workflows, spatial models, interactive maps, dashboards, or cartographic products, with attention to data quality, completeness, limitations, and fitness for purpose to inform leadership decisions;
  • Use of programming or analytic tools such as Python, R, and ArcGIS to transform, analyze, and visualize data for surveillance, preparedness, emergency response, or public health decision-making