Data Scientist (ARTIFICIAL INTELLIGENCE/MACHINE LEARNING)

Serves as an Al (Artificial Intelligence) Testing and Evaluation Data Scientist providing subject matter Al expertise and execution to test and evaluate Al systems.

Provides professional and scientific expertise in the application of data science disciplines for complex studies in machine learning and deep learning algorithms, statistical analysis, visualizations, programing and computer science.

Provides expertise in evaluating and measuring data science and artificial intelligence systems in accordance with data science Lifecyle practices within DoD parameters.

Ensures Al systems are developed in accordance with applicable legal frameworks such as General Data Protection Regulation (GDPR) and National Institute of Standards and Technology (NIST).

Incorporates, Office of Management and Budget (0MB) test and evaluation requirements, DOD Al ethical principles into DLA Al test and evaluation framework to generate an RAI test strategy for modeling cases.

Utilizes expertise to coordinate the integration of the DLA Al testing and evaluation program during the product lifecycle from concept and design inception, as development proceeds, and integrated to ensure effective RAI implementation.

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.