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Mathematical Statistician

3 months ago

Washington, United States Office Of The Inspector General Full time

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.