The GSA Office of Inspector General (OIG) is seeking a highly motivated and qualified Data Scientist for our Cyber and Data Analytics team in the Office of Investigations. We are currently filling one vacancy that will be located in one of the following locations, but additional vacancies may be filled as needed.

Washington, DC Boston, MA Chicago, IL Fort Worth, TX Kansas City, MO Lakewood, CO Philadelphia, PA Tacoma, WA Qualifications:

Starting Pay for all locations will be dependent upon the associated GS-Locality Pay Table for that area. If you are a new federal employee, your starting salary will likely be set at the Step 1 of the grade for which you are selected.

BASIC REQUIREMENTS DATA SCIENTISTS

All candidates for Data Scientists must meet one of the following basic requirements.

A.

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

B.

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. This position has a positive education requirement: Applicants must submit a copy of their college or university transcript(s) and certificates by the closing date of announcements to verify qualifications. If selected, an official transcript will be required prior to appointment.

ADDITIONAL REQUIREMENTS TO QUALIFY AT THE GS-13 LEVEL

In addition to the Basic Requirements listed above, you must have one year of specialized experience equivalent to the GS-12 in the Federal service. Specialized experience is technical data analytics expertise in working with teams to develop data-driven solutions, products and definitions that address program and business challenges.

This experience must include:

Gathering and compiling data from a variety of business data systems; Consulting with diverse stakeholders and using analysis tools to design and implement data analyses; Using appropriate analytic and statistical software to programmatically prepare data for analysis and clean imperfect data; Translating data analyses into meaningful, easily understood communications; Conducting observational analyses using software and/or programming languages including R, Python, Microsoft Power BI, and SQL to explore/group data, test hypotheses, predict outcomes, and inform decisions; Developing automated data solutions (including dashboards and visualizations); and Providing input to management for decisions on an organization's enterprise data environment and/or data management practices.