IT Specialist (APPSW/AI)

Applicants must have IT-related experience demonstrating each of the four competencies listed below:

1. Attention to Detail - Is thorough when performing work and conscientious about attending to detail.
2. Customer Service - Works with clients and customers (that is, any individuals who use or receive the services or products that your work unit produces, including the general public, individuals who work in the agency, other agencies, or organizations outside the Government) to assess their needs, provide information or assistance, resolve their problems, or satisfy their expectations; knows about available products and services; is committed to providing quality products and services.
3. Oral Communication - Expresses information (for example, ideas or facts) to individuals or groups effectively, taking into account the audience and nature of the information (for example, technical, sensitive, controversial); makes clear and convincing oral presentations; listens to others, attends to nonverbal cues, and responds appropriately.
4. Problem Solving - Identifies problems; determines accuracy and relevance of information; uses sound judgment to generate and evaluate alternatives, and to make recommendations.

AND

Applicants must have 52 weeks of specialized experience equivalent to at least the next lower grade level, GS-12 in the Federal Service.

Specialized Experience is the experience that equipped the applicant with the particular knowledge, skills, and abilities (KSA's) to perform the duties of the position successfully, and that is typically in or related to the position to be filled. To be creditable, specialized experience must have been equivalent to at least the next lower grade level.

Qualifying specialized experience for GS-13 includes:

• Experience executing tasks that advance IT opportunities and address critical AI challenges.
• Experience in data preprocessing, feature engineering, and model evaluation techniques to accomplish assignments.
• Experience in software development, software engineering principles, version control systems, debugging, testing, and deployment to build robust and scalable AI systems.
• Experience code to conduct analyses using at least two of the following languages or statistical software or technologies: Python, R, SAS, Stata, Julia, Matlab, Octave, or Spark.