Data Scientist (Direct Hire)

Overview

As a senior Data Scientist, you serve as a technical authority guiding agency data and analytic systems. You lead the design and deployment of advanced statistical and machine learning models, establish standards for data quality and model validation, architect analytic environments, and advise leadership on data and analytic strategy to support mission priorities.

Major Duties

Duties assigned at lower grade levels will be of more limited scope, performed with less independence and limited complexity; duties will be commensurate with the grade of selected employee.,Define agency standards and reference architectures for data and artificial intelligence engineering solutions.,Lead the design, define agency standards and reference architectures for data and artificial intelligence engineering solutions.,Establish machine learning operations practices, including model packaging, deployment, monitoring, and risk controls.,Direct implementation of artificial intelligence governance, privacy protections, and access controls for enterprise data systems.,Architect analytic environments and data designs and guide lineage, documentation, and environment transition practices.,Oversee integration of statistical and machine learning methods into operational systems to ensure reproducibility and security.,Set and oversee data quality, model validation, and documentation standards and monitor organizational compliance.,Lead metadata, catalog stewardship, including tagging, classification, lineage, and certification processes.

Qualifications

Specialized experience is experience that has equipped you with the particular ability, skill, and knowledge to successfully perform the duties of this position and is typically in or related to this line of work. To qualify for GS-14, you must have one year of directly related specialized experience equivalent to the GS-13 level: Leading the design and deployment of statistical or machine learning models and enterprise data pipelines that support mission or program decisions. Establishing organization-wide standards for data quality, model validation, and technical documentation and overseeing adherence to those standards. Developing and implementing machine learning operations practices, including model deployment, monitoring, and governance across multiple environments. Your resume must include a clear and detailed narrative description, in your own words, of how you meet the required specialized experience. Experience statements copied from a position description, vacancy announcement or other reference material constitutes plagiarism and may result in disqualification and losing consideration for the job. Please visit https://www.nasa.gov/careers/how-to-apply/#Artificial-Intelligence to review NASA's guidance on the use of artificial intelligent (AI) or AI-assisted tools during the application process.

Education

Basic Requirement: You must have successfully completed a full 4-year course of study in an accredited college or university leading to a bachelor's or higher degree with a major in mathematics, statistics, computer science, data science or field directly related to the position. OR Have a combination of education and experience equivalent to a major field of study (30 semester hours) equivalent to one of the majors shown above, plus additional education or appropriate experience. U.S. degrees must have been awarded from colleges or universities that are accredited by recognized accrediting organizations. For a list of schools that meet this criteria, go to http://ope.ed.gov/accreditation/. If you are using education completed in foreign colleges or universities to meet the qualification requirements, you must show that the education credentials have been evaluated by a private organization that specializes in interpretation of foreign education programs. These education credentials must be deemed equivalent to that gained in an accredited U.S. education program; or full credit has been given for the courses at a U.S. accredited college or university. For further information, visit: https://sites.ed.gov/international/recognition-of-foreign-qualifications/. All degrees must have been received in the year of, or any year subsequent to the original date of accreditation.