USA remote
Supervisory Data Scientist (Associate Division Chief)
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 GS-15 Candidates must meet the following qualification criteria in order to be deemed as qualified: Education; Specialized Experience; and 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) plus additional education or appropriate experience.
SPECIALIZED EXPERIENCE 1. Leading or overseeing complex, organization-wide data management and/or data governance programs, including the implementation, development, and/or operation of enterprise data catalogues, data warehouses, data lakes, or other data platforms; 2. Overseeing the design, development, implementation, or improvement of enterprise data platforms, large-scale data collections, analytical systems, dashboards, data models, or automated reporting solutions; 3.
Managing the development and implementation of artificial intelligence (AI) or machine learning (ML), including through the use of Large Language Models (LLMs), to facilitate data discovery, enhance data analytics, and/or support data science programs with large, complex datasets; 4. Establishing or implementing data governance, data quality, validation, data management, or analytical standards and processes across multiple programs or organizational components; 5.
Providing technical leadership 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; 6. Coordinating and directing the implementation of data architecture, data frameworks, and technological infrastructure supporting data collections and complex datasets, including those containing large-scale or nationwide geospatial data; 7.