Statistician (Data Scientist)

You must meet the following requirements within 30 days of the closing date of this announcement. For the Statistician (Data Scientist), GS-1530-12 position, you must qualify for one of the following options that best describes how you meet the Individual Occupational Requirement: A.

Degree: that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc.

Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing. OR B.

Combination of education and experience: courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.

AND Meet the following Specialized Experience: For the GS-12, you must have one year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service.

Specialized experience for this position includes: Assisting in researching and compiling data for inspection, audit and investigation activities; AND Supporting data processing and analysis using analytic platforms and software; AND Contributing to the development of work products such as data briefings, dashboards, and presentations based on data analysis. The experience may have been gained in either the public, private sector or volunteer service.

One year of experience refers to full-time work; part-time work is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week on your résumé. If you are a current Federal Employee, in addition to the above requirements, you must meet the following time-in-grade requirement, if applicable: For the GS-12, you must have been at the GS-11 grade level for 52 weeks.

Time After Competitive Appointment: Candidates who are current Federal employees serving on a non-temporary competitive appointment must have served at least three months in that appointment.

At the GS-12 level, this is a developmental position established to provide growth with the complexity of assignments increasing with knowledge and skills. As a/an Statistician (Data Scientist), you will: Serve as a technical expert in a variety of data modeling techniques applying complex data modeling theories and techniques to support projects.

Apply data modeling methods and quantities techniques for the solution of specific problems, analysis and interpretation of data modeling samples; the selection and use of data modeling analysis, operations research or management analysis methods, and the correct use of appropriate computer systems and software to accomplish these assignments.

Conduct theoretical and quasi-experimental investigations to develop new or improve existing theories and techniques for the solution of problems in accuracy, reliability, availability and maintainability and which serve to expand the framework of knowledge in systems analysis. Provide advice and guidance on the appropriate selection and use of data modeling sampling and analysis methods to produce defensible results and survey design and analysis issues.