Data Scientist (AI)

About the role

The Division of Trading and Markets seeks a dynamic Data Science expert for its SK-16 Data Scientist (AI) position. You will use modern data science, quantitative models, and analytical tools to interpret financial and market data, improve workflows, and advance the SEC's data-driven initiatives. This role blends technical, financial, and legal expertise with strong collaboration and communication skills. Applicants 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-16: Applicant must have at least one year of specialized experience equivalent to the GS/SK-14 level: Providing leadership on financial data initiatives, leveraging expertise in data standards, machine-readable languages, and analytical methods to strengthen organizational analytical capabilities; AND Applying AI tools and analytical methods to strengthen evaluation of structured and unstructured data, improving workflow efficiency, and supporting modernization efforts as a recognized technical resource; AND Leading the development and enhancement of data infrastructure to support analytical processing, data ingestion pipelines, and modernization activities across diverse technical platforms, databases and storage architectures including cross platform migrations and transformations; AND Supporting long-range planning, strategic decision making and policy interpretations, using and communicating analytical findings on structured and unstructured data, analytics, and cloud systems to leadership, program staff, and external stakeholders. ACCOMPLISHMENT RECORD COMPETENCIES: Your Accomplishment Record narratives should address the following competencies. See the How You Will Be Evaluated section below for more information: 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. 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. Teamwork and Collaboration - Interacts with internal and external others in a manner that advances SEC goals and objectives. 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.

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Company Intel

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