Candidates must meet the Office of Personnel Management (OPM) educational requirement for Mathematical Statistician. Link to requirement:
OPM requirement: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/1500/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.
We will review your resume, responses to the questionnaire and required documents to ensure you meet the basic qualification requirements. Your resume must address the knowledge, skills, and abilities listed in the Qualifications Section. If you meet basic qualification requirements, your application will be further evaluated. We will compare your resume and supporting documentation to your responses on the assessment questionnaire. We will evaluate your qualifications and eligibility and notify you if you meet minimum qualification requirements. NOTE: We do not require a separate statement responding to the competencies, also referred to as Knowledge, Skills and Abilities (KSAs). However, your resume should clearly show possession of these competencies:
1. Professional knowledge of, and skill in applying, complex analytical, mathematical, and statistical principles, theories, concepts, and methodology of mathematical statistics in order to plan, coordinate, and execute studies of marked difficulty and responsibility as a Division and OE analyst performing assignments involving data science and data mining.
2. Skill in querying very large relational databases and using statistical computer languages such as Python, R, SQL, or SAS.
3. Demonstrated ability to use statistical programming languages to manipulate data and draw insights from large data sets such as Python, R, or SAS.
4. Skill in working with various data architectures and experience with related applications.
5. Skill in using best-practices to organize and manage programming code and experience with code-sharing and distributed version control tools such as GitHub.
6. Skill in using advanced statistical, mathematical, data science, or economic techniques (regression, properties of distributions, statistical tests and proper usage, etc.).
7. Skill in visualizing and presenting data for stakeholders using software packages such as R Shiny, SAS Visual Analytics, Tableau, Periscope, Business Objects, D3, ggplot, or other JavaScript charting libraries.
8. Knowledge of various Python and R libraries for statistical/mathematical analysis and machine learning algorithms such as: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
9. Knowledge of distributed data and computing tools such as Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
10. Knowledge of the fundamental principles of statistics, mathematics, economics, and finance.
11. Skill in making effective oral and written presentations to individuals and groups.
Candidates must have one full year of specialized experience at or equivalent to the GS-09 level. Specialized Experience is defined as: Experience using statistical software, such as SAS, Python, R, STATA, or MATLAB, and extensive experience working with large data. Candidates could also qualify with a PhD or equivalent doctoral degree or 3 full years of progressively higher level graduate education leading to a PhD or equivalent doctoral degree (all educational requirements must be met by closing date of announcement).
This position is included in the bargaining unit.
More than one selection may be made from this announcement, and the office for that selection may vary.
Please note - only your resume and cover letter will be forwarded to the selecting official.
*This announcement will be used to fill vacancies through OPM-Authorized Government-Wide Direct Hire Authority. Category rating, veteran's preference, and traditional rating and ranking of applicants DO NOT APPLY for this vacancy. For more information on OPM's Authorization of Direct Hire Authority, please visit the link below*:
https://www.opm.gov/policy-data-oversight/hiring-information/direct-hire-authority/#url=Governmentwide-Authority