The Office of the Inspector General is one of the best places to work in the Department of Justice and is one of the premier inspector general offices in federal government. We are seeking a highly-motivated professional employee with experience in providing superior customer service in support of our mission to promote integrity, efficiency, and accountability within the Department of Justice.

Duties

The Office of the Inspector General (OIG) in the U.S. Department of Justice (DOJ) is a statutorily created independent entity that works to prevent fraud, waste, abuse, and misconduct in DOJ programs and personnel, and to promote economy and efficiency in those programs. The Office of Data Analytics (ODA) is responsible for supporting the OIG's audits, evaluations, investigations, and special reviews of the personnel and programs of all DOJ components. The goal of the Data Analytics program is to: (1) develop the OIG's capability to manage large datasets to support various OIG projects; (2) develop models to automatically identify indicators of fraud and other high-risk programs and/or transactions; and (3) represent the Department in its interactions with all federal Departments and agencies regarding data analytics activities, policies, standards, and programs. As Mathematical Statistician (Data Scientist), your responsibilities will include, but are not limited to: As a GS-7: Writing basic/routine code in statistical and data science software applications and programming languages to analyze a wide variety of data. Performing basic exploratory data analyses and statistical analyses on large and complex datasets Applying statistical/mathematical methods, such as basic regression analysis, sampling design and estimation, machine learning, geospatial analysis, time series analysis, or other inferential statistics to solve research objectives. Developing sound mathematical/statistical research design to solve basic problems and interpret the results of those solutions. Conveying methodological approaches, analyses, and information in written form, such as technical reports and literature reviews. Conveying methodological approaches, analyses, and information through oral briefings, consultations, and presentations to technical and non-technical audiences. As a GS-9: Writing code in statistical and data science software applications and programming languages to analyze a wide variety of data. Performing basic exploratory data analyses and statistical analyses on large and complex datasets Applying statistical/mathematical methods, such as basic regression analysis, sampling design and estimation, machine learning, geospatial analysis, time series analysis, or other inferential statistics to solve research objectives. Developing sound mathematical/statistical research design to solve problems and interpret the results of those solutions. Conveying methodological approaches, analyses, and information in written form, such as technical reports and literature reviews. Conveying methodological approaches, analyses, and information through oral briefings, consultations, and presentations to technical and non-technical audiences. Responsibilities will increase and assignments will become more complex as your training and experience progress.

Requirements

• You must be a U.S. Citizen or National.
• You must be able to obtain and maintain a security clearance.
• You must be registered for the Selective Service, if applicable.
• You must successfully pass and are subject to random drug screenings.
• You must meet all qualification requirements by the closing date of this announcement.
• You may be subject to a probationary period.
• Candidates may be eligible for the Federal Student Loan Repayment Program.

Qualifications

Education Requirements Mathematical Statistics Series 1529: A. 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 B. 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. AND GS-7 Specialized Experience: Your resume must display that you possess One year (52 weeks) of the below specialized experience at least equivalent to the GS-1529-5 Mathematical Statistician (Data Scientist) position. Examples of specialized experience includes: Writing routine/basic code in a widely used statistical/data science software application or equivalent programming languages (e.g., R, Python, or equivalent) and applying statistical methods, such as basic regression analysis, sampling design and estimation, machine learning, geospatial analysis, time series analysis, or other inferential statistics to solve research objectives. The specialized experience described above must be identifiable in your submitted resume. OR 1 year of graduate-level education or superior academic achievement. GS-9 Specialized Experience: Your resume must display that you possess One year (52 weeks) of the below specialized experience at least equivalent to the GS-1529-7 Mathematical Statistician (Data Scientist) position. Examples of specialized experience include: Writing code in a widely used statistical/data science software application or equivalent programming languages (e.g., Python, R or equivalent) and applying statistical and mathematical methods, such as basic regression analysis, sampling design and estimation, machine learning, geospatial analysis, time series analysis, or other inferential statistics to solve research objectives.OR2 years of progressively higher level graduate education leading to a master's degree or master's or equivalent graduate degree. You must meet the job announcement requirements by the closing date.

Education

All academic degrees and coursework must be completed at a college or university that has obtained accreditation or pre-accreditation status from an accrediting body recognized by the U.S. Department of Education. For a list of schools that meet this criteria, see www.ed.gov. For foreign education, see: http://www.ed.gov/about/offices/list/ous/international/usnei/us/edlite-visitus-forrecog.html.

**NOTE: You must submit a copy of your unofficial transcript that supports the positive education requirement.

Contacts

• Address Audit Division 950 Pennsylvania Ave NW Washington, DC 20530 US
• Name: Office of Human Resources
• Phone: 20261604501
• Email: [email protected]