Jobs · Engineering · North Carolina

Lead Data Scientist

TWU-Center for Women Entrepreneurs · Greensboro, North Carolina, United States · Today
EngineeringFull-time
Location: ATLANTA, GA***THIS POSITION IS NOT REMOTE*** ***U.S. Citizenship required*** ***This job will close when we have received 150 applications which may be sooner than the closing date.*** OPEN TO THE PUBLIC What You’ll Be Doing Day To Day As a Lead Data Scientist, you will: Serve as a data science expert in the analysis and classification of public health surveillance, research, and administrative health data; and serve as Team Lead for a team of data scientists.Consult and collaborate with statistical, data science, artificial intelligence and public health professionals in the collection, linkage, processing, mining, coding, classification, and analysis of public health surveillance, research, and administrative health data.Assist in preparing comprehensive reports that include discussion of substantive issues related to data science methodology for public health surveillance and related applications, assessment of the adequacy and quality of data used in the analyses, and explanation of the methods, results, and relevance to the health issue under study. Qualifications WHAT WE ARE LOOKING FOR Basic Qualifications 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 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. AND Minimum Qualifications: You must have one year of specialized experience to perform successfully the duties of the position. To be creditable, specialized experience must have been equivalent to at least the GS-13 grade level in the Federal service performing ALL of the following: Performing data science work that requires knowledge of public health data systems, converting data, and proficiency data science;Developing and analyzing structured and unstructured data; andUnderstanding of data science methods (e.g., machine learning, natural language processing).

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