Data Scientist, CG-1560-13/14

Qualifying experience may be obtained in the private or public sector. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g. Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic, religious spiritual; community; student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience. Additional qualifications information can be found here. Basic Requirements: 1. 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 – 2. 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. In addition to meeting the Basic Requirements above, applicants may qualify based on specialized experience: CG-13: Applicants must have completed at least one year of specialized experience equivalent to at least the CG/GS-12 level or above in the Federal service. Specialized experience is experience 1) developing data analytic solutions using machine learning and artificial intelligence techniques; 2) conducting analyses using software and/or programming languages that include SQL, Python, R or Apache Spark to test hypotheses, predict outcomes, and deliver data reports to stakeholders; and 3) managing and processing large datasets into structured formats for matching, reporting and analysis. CG-14: Applicants must have completed at least one year of specialized experience equivalent to at least the CG/GS-13 level or above in the Federal service. Specialized experience is experience 1) developing data analytic solutions using machine learning and artificial intelligence techniques; 2) conducting analyses using software and/or programming languages that include SQL, Python, R, Databricks and/or Apache Spark to test hypotheses, predict outcomes, and deliver data reports to stakeholders; 3) managing and processing large datasets into structured formats for matching, reporting and analysis; and 4) creating and maintaining data delivery pipelines.
This position is in the Division of Insurance and Research, Large Data Management Section leading the performance of complex analytics, including the use of machine learning and artificial intelligence techniques, on large datasets to support the mission of the division and the Corporation. Additional selections may be made from this vacancy announcement to fill identical vacancies that occur subsequent to this announcement.