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This Government Contract opportunity from Colorado was posted on May 22, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Data Analytics and Predictive Modeling

Closed
State & Local

Contract Overview

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The contract involves developing predictive models using institutional data to forecast enrollment trends, assess financial aid impacts, and identify retention risks. The scope includes not only building these models but also providing a complete handoff with thorough documentation to ensure the institution can independently utilize and maintain the models after project completion. This subcontract falls under NAICS code 541620, which relates to environmental consulting services that typically encompass analytical and modeling work. Issued by the Auraria Higher Education Center in Colorado, the contract was posted on May 22, 2026, with a response deadline of May 27, 2026. Although specific location details and points of contact were not provided, the focus is clearly on supporting higher education analytics through data-driven predictive insights aimed at improving strategic decision-making related to enrollment and student retention. The contract represents an opportunity to deliver advanced data solutions that directly inform institutional planning and support services.

General Info

Develop predictive enrollment models, assess financial aid and retention, with full documentation handoff.

Agency

Colorado → Auraria Higher Education Center

NAICS

541620 - Environmental Consulting ServicesView NAICS

Place of Performance

Not specified

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyColorado → Auraria Higher Education Center
ContactsNo contacts available
OfficeN/A
Organization / Agency
Colorado → Auraria Higher Education Center
Office AddressN/A
ContactsNo contact information available

Full Description

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Build predictive models using institutional data to forecast enrollment trends, aid impacts, and retention risks, with full handoff of models and documentation.