About this role
Job SummaryThe Division of Economic and Risk Analysis is seeking a Data Scientist (AI) in the Office of Data Standards and Innovation. As a Data Scientist (AI), you will help maintain operational continuity, supports modernization initiatives, and strengthen the Commission's ability to provide investors, regulators, and the public with consistent and accessible machine-readable data.
QualificationsApplicants are responsible for confirming all required materials are submitted by the closing date of the announcement. Please check the How You Will Be Evaluated and Required Documents sections carefully, as missing documents will render the application incomplete and ineligible for review. Qualifying experience may be obtained in the private or public sector. 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. All qualification requirements must be met by the closing date of this announcement. BASIC REQUIREMENT: 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 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. MINIMUM QUALIFICATION REQUIREMENT: In addition to meeting the basic requirement, applicants must also meet the minimum qualification requirement. SK-14: Applicant must have at least one year of specialized experience equivalent to the GS/SK-13 level: A. Managing structured and financial data initiatives, establishing data standards, and recommending AI/ML tools to enhance organizational capabilities. B. Using AI-enabled tools and automation to improve data analysis, streamline workflows, and support modernization projects; recognized as a technical expert in these applications. C. Designing and maintaining cloud or hybrid systems that support data processing, validation, storage, and transformation across multiple platforms and databases. D. Translating analytical findings into actionable insights for leadership, program teams, and external partners; contributing to data strategy and policy decisions. ACCOMPLISHMENT RECORD COMPETENCIES: Your Accomplishment Record narratives should address the following competencies. See the How You Will Be Evaluated section below for more information: Competency 1: AI/ML Application & Responsible Use - Uses appropriate AI/ML methods and tools - including code assist and information processing automation to enhance analysis of structured data, increase workflow efficiency, and modernize analytical or review processes while following responsible AI practices. Competency 2: Technology Awareness and Innovation: Maintains awareness of emerging analytics and AI/ML technologies and uses this knowledge to introduce and share relevant advancements that strengthen organizational capabilities. Competency 3: Teamwork and Collaboration: Interacts with internal and external others in a manner that advances SEC goals and objectives. Competency 4: Technical Quality and Reproducibility - Applies structured engineering practices and quality control techniques and methods across the development lifecycle, producing well documented code, maintaining version controlled artifacts, and creating reproducible workflows
Major DutiesIn this role as a Data Scientist (AI), you will be responsible for: Providing authoritative guidance on structured data standards, disclosure requirements, validation rules, and data quality principles. Evaluating the structure, consistency, and interpretability of machine-readable disclosures submitted to the Commission. Conducting complex analytical assessments, identifying structural or semantic issues, and determining appropriate methodological approaches. Supporting the development, refinement, and implementation of taxonomy elements, data models, and validation logic. Participating in long-range planning related to structured data modernization, standard setting, and statutory implementation. Collaborating with staff across the SEC, other regulators, and external standards groups to address data quality and structured reporting issues. Designing or advising on processes, tools, or automation approaches that improve machine-readable disclosure quality and usability.