Data Scientist

Duties include, but are not limited to, the following: Participates in planning, designing, developing, and implementing state-of-the-art data science applications, models, technologies, and guiding principles for data use and analysis in direct support of the Bureau of Labor Statistics mission and programs Coordinates and integrates activities on the exploration, acquisition, development, and implementation of data science tools and applications Analyzes a variety of structured and unstructured data sources to provide data-informed insights to the organization to streamline processes and evaluate the effectiveness of the program operations in meeting established goals and objectives Identifies data science requirements within the organization to support ongoing program activities Develops new user interfaces and adapts tools for displaying scientific information in specialized databases

Basic Requirement Data Scientist, 1560: 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 B) Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience.

Specialized Experience 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. GS-12: In addition to the basic requirements above, applicants must have at least 52 weeks of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 in the federal service.

Experience for this position includes at least three of the following: Maintaining machine learning, natural language processing, and/or artificial intelligence systems in production; Assisting in research and evaluation of the state-of-the-art topics in data science, such as deep learning and large language models; Using data engineering techniques to process large, complex datasets into structured formats for record matching, anomaly detection, data analysis, and/or estimation; Writing high-quality, maintainable code for analytics and applications using the Python programming language.