Data Scientist (Artificial Intelligence/Machine Learning)

Full Job Description

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.

Or Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience. AND 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 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 AI.

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 AI systems are designed for auditability to manage AI risk assessment policies and principles which guide automated decisions supporting DLA business operations.

Provides expert advice to senior leadership and AI stakeholders to adopt new or revised policy and implementation plans resulting from AI test and evaluation integration.

Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for AI testing and evaluation. C.

Education: Applicants may not qualify for this position based on education in lieu of specialized experience.

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. Major Duties:

• Serves as an AI (Artificial Intelligence) Testing and Evaluation Data Scientist providing subject matter AI expertise and execution to test and evaluate AI 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 AI 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 (OMB) test and evaluation requirements, DOD AI ethical principles into DLA AI test and evaluation framework to generate an RAI test strategy for modeling cases.
• Utilizes expertise to coordinate the integration of the DLA AI testing and evaluation program during the product lifecycle from concept and design inception, as development proceeds, and integrated to ensure effective RAI implementation.