USA remote
Data Scientist
About this role
The qualifications for this position must be met by 11:59 PM (Eastern Time) on 11/02/2026. Time in Grade does not apply to Delegated Examining Announcements, any reference to Time in Grade in the questionnaire will not apply to the rating and ranking of applicants. Application Limit: This vacancy is limited to the first 75 applications received. All applications received prior to midnight 11:59 PM (ET) of the day the application limit is reached will be accepted and considered.
If the application limit is not reached by the closing date of the announcement, all applications received during the open period will be considered. Any required documents must be submitted at the time that you apply as documents will not be accepted past the day the application limit is reached, if applicable. If you choose to edit your application after it has been submitted, it will be removed from consideration until you re-submit your application.
The date your application is last submitted will be used to determine whether you meet the cut-off criteria. Basic Requirements: All applicants must meet the following basic requirements: (Must be supported in Transcripts from an accredited institution, Resume and/or Applicable Certificate) 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. GS-07: You qualify at the GS-07 level if you possess one (1) year of specialized experience, which is equivalent to at least the GS-05 level in the federal government, that equipped you with the skills needed to successfully perform the duties of the position.
You must have experience performing the majority of the following duties: Assisting with the collection, cleaning, and organization of data for analysis; Supporting data analysis using statistical methods and software tools under supervision; Preparing data visualizations and reports to communicate findings to team members; and, Utilizing programming languages (such as Python, R, or SQL) to perform routine data manipulation and analysis tasks.