Support for Creating a Public Dataset for the Department of Education’s Gainful Employment / Financial Value Transparency

Closed Solicitation Posted

Solicitation number
RFQ2032H824Q00037
Agency
Responses due
Set-aside
Total Small Business

Opportunity facts

Place of performance
Washington, District of Columbia, United States

Notice details come from SAM.gov. Updated .

About this opportunity

The Internal Revenue Service (IRS), Statistics of Income Division (SOI), is seeking contractor support to apply statistical disclosure limitation methodology based on differentially private algorithms to produce a private dataset for the Department of Education's Gainful Employment / Financial Value Transparency (GE/FVT) regulation. The contractor shall provide support to develop a calculator tool through which IRS-SOI can release multiple datasets comprising both counts and medians broken down by attributes (e.g., college, program), while maintaining the confidentiality of Federal Tax Information. This is a firm fixed price requirement with a one-year period of performance from September 1, 2024 to August 31, 2025.

This procurement is 100% set aside for small businesses under NAICS code 541690 - Other Scientific and Technical Consulting Services, with a $19 million size standard. The place of performance is Washington, DC. There are no known incumbent contractors, and the budget range is not specified. The quotation due date is August 14, 2024 at 12:00 ET.

Notice text

The Internal Revenue Service (IRS), Statistics of Income Division (SOI), requires contractor support to apply statistical disclosure limitation methodology based on differentially private algorithms (code to run Python) to support the production of a private dataset for the Department of Education Gainful Employment / Financial Value Transparency (GE/FVT) regulation.

The contractor shall provide support to develop a calculator tool through which IRS-Statistics of Income Division (SOI) can release multiple datasets comprising both counts and medians broken down by attributes (e.g., median earnings by college, program, etc.) under a common differentially privacy budget (epsilon). The results will maintain the confidentiality of Federal Tax Information (FTI), such that the output can be released to the Department of Education.

Files

File Type Posted
RFQ 2032H8-24-Q-00037 Amend 00001.pdf PDF
RFQ 2032H8-24-Q-00037 (7-24-24).pdf PDF

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