Data Scientist (Artificial Intelligence/Machine Learning)

About the role

See below for important information regarding this job. Position will be filled at any of the locations listed below. Site specific salary information as follows: Battle Creek, MI: $125,776- $163,514 Columbus, OH: $131,245- $170,624 Dayton, OH: $130,461 - $169,604 Fort Belvoir, VA: $143,913- $187,093 New Cumberland, PA: $143,913- $187,093 Ogden, UT: $125,776- $163,514 Philadelphia, PA: $138,595- $180,178 Richmond, VA: $131,385- $170,806 To qualify for a Data Scientist (Artificial Intelligence/Machine Learning), your resume and supporting documentation must support: A. 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. B. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-aftercompetitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes: Conducts large, agency wide, research and development reviews of metrics, measurements, and evaluation methods for emerging and existing areas of Al. Utilizes data science expertise to develop algorithms and tools to support data manipulation and processing as well as the use of data visualization techniques to articulate high risk findings. Ensures the Al systems are designed for auditability to manage Al risk assessment policies and principles which guide automated decisions supporting DLA business operations. Provides expert advice to senior leadership and Al stakeholders to adopt new or revised policy and implementation plans resulting from Al test and evaluation integration. Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for Al testing and evaluation. 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.