Interdisciplinary Engineer/Scientist

You may qualify at the GS GS-14, if you fulfill the following qualifications: A. One year of specialized experience equivalent to the GS-13 grade level in the Federal service as listed below: 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. Leading strategic planning, requirements refinement, research, design, and architecting of AI/ML-enabled data solutions, technology roadmaps overseeing the development, integration, testing and transitioning of advanced analytics and machine learning systems in support of a large-scale, data-intensive environment. Designing and implementing software and data pipelines compliant with Risk Management Framework (RMF) and simulation interoperability standards, and applying methods from data science, AI/ML, physical sciences, geography, and social sciences to deliver mission-driven analytic capabilities. Knowledge of data schemas, ontologies, and experience working with standards to provide advice and guidance. Knowledge of principles, practices, and processes required for data collection, manipulation, cleaning, transformation, analysis and visualization to drive decisions for the Department of Defense or other large organizations. Substitution of education may not be used in lieu of specialized experience for this grade level. In addition to meeting qualifications, your application package must reflect the applicable experience to meet the Individual Occupational Requirements for the 0801/0854/1301/1550, series as listed below: Leading strategic planning, requirements refinement, research, design, and architecting of AI/ML-enabled data solutions, technology roadmaps overseeing the development, integration, testing and transitioning of advanced analytics and machine learning systems in support of a large-scale, data-intensive environment. For the 0801-0854 Series: Degree: a professional engineering. To be acceptable, the curriculum must: (1) be in a school of engineering with at least one curriculum accredited by the Accreditation Board for Engineering and Technology (ABET) as a professional engineering curriculum; or (2) include differential and integral calculus and courses (more advanced than first-year physics and chemistry) in five of the following seven areas of engineering science or physics: (a) statics, dynamics; (b) strength of materials (stress-strain relationships); (c) fluid mechanics, hydraulics; (d) thermodynamics; (e) electrical fields and circuits; (f) nature and properties of materials (relating particle and aggregate structure to properties); and (g) any other comparable area of fundamental engineering science or physics, such as optics, heat transfer, soil mechanics, or electronics. OR a Combination of education and experience -- college-level education, training, and/or technical experience that furnished (1) a thorough knowledge of the physical and mathematical sciences underlying professional engineering, and (2) a good understanding, both theoretical and practical, of the engineering sciences and techniques and their applications to one of the branches of engineering. For the 1301 Series Degree: physical science, engineering, or mathematics that included 24 semester hours in physical science and/or related engineering science such as mechanics, dynamics, properties of materials, and electronics. OR a Combination of education and experience -- education equivalent to one of the majors shown in A above that included at least 24 semester hours in physical science and/or related engineering science, plus appropriate experience or additional education. For the 1550 Series-Degree: Bachelor's degree in computer science or bachelor's degree with 30 semester hours in a combination of mathematics, statistics, and computer science. At least 15 of the 30 semester hours must have included any combination of statistics and mathematics that included differential and integral calculus. All academic degrees and course work must be from accredited or pre-accredited institutions. *NOTE: Failure to provide transcripts will result in you being rated ineligible for this position. This position is part of the Organization of the Joint Chiefs of Staff, Joint Chiefs of Staff. The incumbent will be responsible for advancing the organization's mission by leading data and artificial intelligence (AI) initiatives and facilitating, coordinating, and executing professional scientific functions to store, manipulate, transform and present information by means of computer systems.