USA remote
Data Scientist (Data/AI Architect)
About this role
Interested candidates should be passionate about the ideals of our American republic, committed to upholding the rule of law and the U.S. Constitution, and committed to improving the efficiency of the Federal government. Hiring decisions will not be based on race, sex, color, religion, or national origin. Applicants must meet eligibility and qualification requirements by the closing date of this announcement. Time in grade restrictions do not apply to Direct Hire procedures.
QUALIFICATION REQUIREMENTS In order to be deemed as qualified candidates must meet all of the following criteria: education, specialized experience and the required competencies. Education-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 here plus additional education or appropriate experience.
Transcripts must be submitted by the closing date of the announcement. If transcripts are not submitted, the application will be rated as ineligible. Specialized Experience GS-13 Candidates must have one year of specialized experience which is equivalent to the GS-12 grade level in the Federal service. Specialized experience is defined as follows: 1. Designing and supporting complex, organization-wide data management, data governance, and/or data presentation architecture, including enterprise data catalogues, data warehouses, data lakes, or other data platforms; 2.
Developing and implementing artificial intelligence (AI) or machine learning (ML) tools to facilitate data discovery, enhance data analytics, and/or support data science programs with large, complex datasets; 3. Providing technical support in the use of advanced statistical, analytical, computational, or data science methods to identify trends, evaluate data quality, solve complex problems, and support organizational or policy decisions; 4.
Advising stakeholders on complex data, analytical, technical, or program issues and translating technical findings into clear recommendations for technical and non-technical audiences; and 5. Providing data subject matter expertise as part of multidisciplinary teams and projects involving data scientists, analysts, information technology professionals, project managers, contractors, or other technical and professional staff.