Summary This position is located within the Office of Planning, Analysis, and Risk Management (OPARM). OPARM is the FSIS centralized analytics group and tasked with integrating and analyzing relational data. The program also provides data visualization and analytics services to support FSIS decision-making, policy development, risk management, and strategic planning. Responsibilities Perform data cleaning and visualization. Perform trend analysis and algorithm development. Develop new prescriptive analytics used in decision making. Present alternate solutions to analytics and future concepts. Develop statistical models and machine learning models. Analyzes outputs from analyses. Leads the design for data enhancement. Performs quality checks for statistical inference. Provides education on new approaches to data analysis. Develops recommendations for data collection activities and data integration. Maintains knowledge of science based analytical processes. Requirements Conditions of Employment Qualifications Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement including specialized experience and/or education, as defined below. For the GS-14 grade level: Applicants must have one year of specialized experience (equivalent to the GS-13 grade level) that demonstrates: Using Python or R in support of data analytics projects. Developing and executing approaches for analyzing, interpreting, visualizing, and verifying complex data and analyses. Leading projects by establishing objectives, assigning responsibilities, reviewing deliverables, and offering expert guidance on analytical programming, statistical techniques, and data visualization strategies. Developing oral and written presentations communicating complex and technical analyses to inform, influence, and persuade a variety of audiences. 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 and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience. Education Mathematical Statistics Series 1529 Basic Requirements: Degree: that included 24 semester hours of mathematics and statistics, of which at least 12 semester hours were in mathematics and 6 semester hours were in statistics. or Combination of education and experience: at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as shown in A above, plus appropriate experience or additional education. Evaluation of Education: Courses acceptable toward meeting the mathematics course requirement of paragraphs A or B above must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement. Evaluation of Experience: The experience offered in combination with educational courses to meet the requirements in paragraph B above should include evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance. Without other indications of statistical experience, work required in the processing of numerical or quantified information by other than statistical methods is not considered appropriate qualifying experience. Examples of such nonqualifying work include statistical clerical work; statistical drafting; calculation of totals, averages, percentages, or other arithmetic summations; preparation of simple tables or charts; or verification of data by simple comparison or proofreading. Click here for more information on this series: OPM Mathematical Statistics Series 1529 Computer Science Series 1550 Series Definition: This series includes professional positions which primarily involve the application of, or research into, computer science methods and techniques to store, manipulate, transform or present information by means of computer systems. The primary requirements of the work are (a) professional competence in applying the theoretical foundations of computer science, including computer system architecture and system software organization, the representation and transformation of information structures, and the theoretical models for such representations and transformations; (b) specialized knowledge of the design characteristics, limitations, and potential applications of systems having the ability to transform information, and of broad areas of applications of computing which have common structures, processes, and techniques; and (c) knowledge of relevant mathematical and statistical sciences. Basic Requirements: 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. Evaluation of Education: Applicants should have sufficient knowledge to understand the fundamental concepts and techniques of computer science. Courses designed to provide an introduction to computer science techniques and methodologies, to problems of system design, and to other specialized fields are acceptable. Courses or experience in teaching elementary, business, or shop mathematics are not acceptable. Click here for more information on this series: OPM Computer Science Series 1550 Data Science Series 1560 Basic Requirements: 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. Click here for more information on this series: OPM Data Science Series 1560 Additional Information Career Transition Assistance Plan (CTAP), Reemployment Priority List (RPL), or Interagency Career Transition Assistance Plan (ICTAP): Visit the OPM website for information on how to apply as a CTAP, RPL, or ICTAP eligible. To exercise selection priority for this vacancy, CTAP/RPL/ICTAP candidates must meet the basic eligibility requirements and all selective factors. CTAP/ICTAP candidates must be rated and determined to be well qualified (or above) based on an evaluation of the competencies listed in the How You Will Be Evaluated section. When assessed through a score-based category rating method, CTAP/ICTAP applicants must receive a rating of at least 85 out of a possible 100. Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact: USDA's TARGET Center at 202-720-2600 (voice and TDD). It is the policy of the Government not to deny employment simply because an individual has been unemployed or has had financial difficulties that have arisen through no fault of their own. To see more information visit CHCO Council. This announcement may be used to fill additional like vacancies should any occur in the announced duty location(s).
