Supervisory Data Scientist (AI/ML)

Serves as the Branch Chief l responsible for leading enterprise artificial intelligence (AI) and analytics planning, requirements engineering, solution architecture, and value realization activities.

Directs a multidisciplinary team of technical professionals, including solutions architects, data scientists, and cybersecurity engineers, to identify, evaluate, and prioritize AI and analytics initiatives aligned with organizational objectives.

Oversees enterprise use case analysis, technical feasibility assessments, investment planning, and return-on-investment measurements for advanced technology capabilities.

Provides authoritative technical leadership on AI, machine learning, cloud-based analytics platforms, data architecture, and digital transformation strategies

Advises the Artificial Intelligence Officer (AIO) on technology investments, capability roadmaps, and enterprise modernization efforts to improve mission effectiveness, operational efficiency, and decision advantage

To qualify for a Supervisory Data Scientist (AI/ML), your resume and supporting documentation must support: 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. AND B.

Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position.

To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector.

Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-after-competitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement.

Creditable specialized experience includes: - Leads enterprise AI and analytics portfolio planning activities by translating strategic objectives into executable roadmaps, capability development plans, investment strategies, and implementation priorities. - Establishes processes for evaluating, prioritizing, and sequencing AI and analytics initiatives based on mission impact, technical feasibility, organizational readiness prior to development, and return on investment (ROI). - Directs the requirements engineering and solution analysis function for AI, machine learning (ML), Generative AI (GenAI), predictive analytics, and data-driven modernization efforts. - Establishes technical standards, engineering practices, and architectural patterns supporting enterprise AI and analytics intake, framework selection, and architectural design.

OR C. 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.

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.