DATA SCIENTIST (DATA ARCHITECT/DATA ENGINEER/AI-ML SPECIALIST)

About this role

This position has a Basic Requirement for the 1560: 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.

*NOTE: Failure to provide transcripts will result in you being rated ineligible for this position. The experience described in your resume will be evaluated and screened from the Office of Personnel Management's (OPMs) basic qualifications requirements. See: Data Science Series 1560 for OPM qualification standards, competencies and specialized experience needed to perform the duties of the position as described in the MAJOR DUTIES and QUALIFICATIONS sections of this announcement by 11/13/2026 Applicant must have directly applicable experience that demonstrates the possession of the knowledge, skills, abilities and competencies necessary for immediate success in the position.

Qualifying experience may have been acquired in any public or private sector job, but will clearly demonstrate past experience in the application of the particular competencies/knowledge, skills and abilities necessary to successfully perform the duties of the position. For the GG-11 You must have specialized experience sufficient to demonstrate that you have acquired all the competencies necessary to perform at a level equivalent in difficulty, responsibility, and complexity to the next lower grade GS/GG-09 in the Federal service and are prepared to take on greater responsibility.

Generally, this would include one year or more of such specialized experience. Specialized experience for this position includes: Assisting in applying statistical, machine learning, natural language processing, or other advanced analytical methods to solve problems involving structured and unstructured data. Supporting the design, development, and validation of predictive models, quantitative analyses, and data-driven decision-support products under guidance.