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Data Scientist (Artificial Intelligence/Machine Learning): DLA

Oct 13, 2025   |   Location: Across The United State of America   |   Deadline: Oct 14, 2025

Experience: Senior

Continent: North America

Salary: $124,531 - $185,234 per year. The specific salary depends on the location.

The Defense Logistics Agency (DLA) is seeking a Data Scientist to serve as an expert in Artificial Intelligence (AI) Testing and Evaluation. The role involves providing professional and scientific expertise in applying data science disciplines to test and evaluate AI systems, ensuring they are developed and implemented in accordance with DoD parameters and ethical principles.

Important Notes
Must be a U.S. citizen.

A Secret security clearance is required.

The appointment is subject to a favorable background check.

A drug test is required.

Responsibilities
Serve as an AI Testing and Evaluation Data Scientist, providing subject matter expertise for testing and evaluating AI systems.

Apply expertise in machine learning, deep learning algorithms, statistical analysis, and computer science for complex studies.

Evaluate and measure AI systems according to the data science lifecycle and DoD parameters.

Ensure AI systems are developed in accordance with legal frameworks like GDPR and NIST, as well as DoD AI ethical principles.

Integrate AI testing and evaluation throughout the product lifecycle, from concept and design to implementation.

Requirements
Education: A degree in Mathematics, statistics, computer science, data science, or a directly related field.

Specialized Experience: One year of specialized experience equivalent to the GS-13 level. This includes experience such as:

Conducting large-scale research and development reviews of metrics and evaluation methods for AI.

Using data science expertise to develop algorithms and tools for data manipulation and visualization.

Ensuring AI systems are designed for auditability and managing AI risk assessment policies.

Providing expert advice to senior leadership and AI stakeholders on policy and implementation plans.

Assessing data quality and establishing standards for AI testing and evaluation.
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