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To qualify for a Data Scientist (Supply Chain), your resume and supporting documentation must support: A. Basic Requirement: Degree in 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 the paragraph above, plus additional education or appropriate experience. 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-13 level, applicants must possess one year of specialized experience equivalent to the GS-12 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes: Serving as a senior analyst in an organization responsible for interpreting extremely unstructured large data sets to develop risk assessment models and methods. Designing and developing the most appropriate techniques to solve problems, enhance performance, and increase efficiency/effectiveness. Designing and building models for standard, non-complex simulations, and utilizing standard-type models to simulate real world environments. Utilizing a wide range of supply chain security risk assessment methods and techniques to recommend those suitable for producing explicit findings and discriminating evaluations. Demonstrating expert knowledge of standard and innovative data science, artificial intelligence, system analysis, risk analysis, predictive analysis, complex computer simulation, program/project planning, and controls techniques. 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.
Solving problems encountered in the gathering, conditioning, analysis, and integration of large and heterogenous volumes of data related to supply chain security risk assessments.
Applying scientific methods, including but not limited to, decision tree analytics, probability to research and improve supply chain risk assessment processes and develop the associated models, policies, and procedures for DLA.
Applying scientific methods, including but not limited to, game theory and statistical analysis, to research and improve supply chain risk assessment processes and develop the associated models, policies, and procedures for DLA.
Performing professional work in data science, artificial intelligence, system analysis, risk analysis, predictive analysis, complex computer simulation, program/project planning and controls, and other related areas.
Providing technical direction, planning, and leadership to create and implement new agency data and supply chain risk assessment policies and processes.
Formulating and developing sophisticated models and techniques for quantitative evaluation and assessment of supply chain risks and their effect on accomplishing agency and customer missions.
Preparing comprehensive technical reports of completed assessments assuring adequate correlation of data, integration of all pertinent considerations, and substantiation of conclusions.
Preparing, presenting, and defending project briefings/recommendations to senior government and commercial industry personnel.