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Technical Information Specialist (Data Analyst / Senior Data Analyst)(Temporary

Library of Congress
Washington, DC Temporary
POSTED ON 5/16/2024 CLOSED ON 6/1/2024

What are the responsibilities and job description for the Technical Information Specialist (Data Analyst / Senior Data Analyst)(Temporary position at Library of Congress?

180 days ( U.S. Citizens Only ) Technical Information Specialist (Data Analyst / Senior Data Analyst)(Temporary Position)
  • Opening Date: February 21, 2024
  • Closing Date: May 31, 2024
  • LC Organization Unit: Office of the Chief Operating Officer
  • LC Organization Unit - Specific Office: Federal Research Division
  • Grade: GS-05/07/09/11/12
  • Series: 1412
  • Availability: U.S. Citizens Only
  • Telework Eligibility: Remote
  • Duration: Temporary, Not-to-Exceed 180 days

The Federal Research Division is offering an opportunity for a qualified individual to serve on a full- or part-time, 180-day appointment as a Data Analyst or Senior Data Analyst. The Federal Research Division conducts research, analysis, and translations for the federal government and qualified contractors.

The selected candidate will perform research responsibilities in support of a broad range of executive and legislative branch agencies, including the Library of Congress and the Congressional Office of International Leadership.

Work Schedule: Full or Part Time - Flexitime

Relocation expenses will not be authorized for the person(s) selected under this announcement.

Multiple vacancies in the following locations: Washington, DC

Position Responsibilities

The Data Analyst or Senior Data Analyst's specific work assignments will include: (1) improving existing methodologies and developing solutions to process and analyze large datasets, including unstructured text and (2) analyzing the statistical validity and integrity of existing research reports.

Under the direction of section heads and project managers, the selected candidate will support division data analysis efforts. Specifically, the appointment may require:

  • Designing and implementing solutions for cleaning, combining, analyzing, and displaying large and disparate datasets and unstructured data using the R programming language.
  • Using advanced data management and analytical skills to create solutions and make recommendations to senior research staff.
  • Troubleshooting issues with data aggregation, structure, and queries.
  • Reviewing data inputs and outputs and ensuring accuracy of both.
  • Making recommendations to improve processes and procedures related to data cleaning, analysis, and display.
  • Creating reports and visualizations that can easily be interpreted and understood by researchers, project managers, and division leadership.
  • Reviewing existing statistical datasets, study designs, and reported findings and determines research integrity, statistical validity, and practical significance of results.
  • Documenting methodologies and clearly and concisely presenting findings to senior research staff.
  • Implementing best practices in design and collection of information to ensure accuracy and validity of results.
  • Authoring reports reflecting analytical findings.
  • Supporting refinements to and expanding capabilities of internal data systems and processes.

The selected candidate will also be expected to support the Division's general research and analysis activities on behalf of federal client agencies. Specifically, the appointment may require:

  • Using Library of Congress collections and open source materials in conducting research.
  • Screening publications, electronic resources, and topics pertaining to a specialized field, in foreign and domestic arenas.
  • Recommending suitable quantitative and qualitative research methodologies.
  • Analyzing qualitative research findings in context of sophisticated conceptual frameworks.
  • Preparing high-quality written products, including report-length documents and abstracts.

Qualifications

Strongly desired (all grades): Advanced proficiency in the R programming language/environment.

Required (all grades): A full 4-year course of study that meets all the requirements for a bachelor's degree with major study in the subject-matter field of the position to be filled.

or

Four years of experience that provided a knowledge of the basic principles, theories, practices, techniques, and terminology of a discipline or subject-matter field; an understanding of the standard methods, procedures, and techniques of research and analysis in the subject-matter field; and where appropriate, ability to read and comprehend nontechnical material in one or more foreign languages. Such experience must have been equivalent to that which would have been gained through a 4-year college curriculum.

or

A combination of education and experience as described above.

Required (GS-07): One full year of graduate level education related to the position or superior academic achievement and/or one year of relevant professional experience equivalent to at least a GS-05.

Required (GS-09): Master's degree or equivalent or two years of progressively higher level graduate education in statistics, economics, or related field and/or at least one year of relevant professional experience equivalent to at least a GS-07.

Required (GS-11): PhD or three years of progressively higher level graduate education in statistics, economics, or related field and/or one year of relevant professional experience equivalent to at least a GS-09.

Required (GS-12): At least one year of relevant professional experience in a similar role equivalent to the GS-11 grade level.

Interested candidates should prepare a resume and a cover letting expressing interest in this opportunity, along with a description of their qualifications that includes work experience and training related to the stated responsibilities. Competitive candidates may be asked to conduct a writing exercise.

Interested candidates should submit their resume and short statement to FRDJobs@loc.gov using the subject heading "Data Analyst Application." Applicant information will be reviewed on a rolling basis and the qualified candidates will be contacted for interviews according to staffing needs. The selection will be based on how well the candidates meet the knowledge, skills, and abilities required.

 

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