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This Government Contract opportunity from Department Of Defense was posted on June 8, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Advanced Analytics, AI/ML, and Probability Modeling

Closed
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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NAICS: 541620
New
Federal
B--ONYX RANCH SVRA PROJECT
Solicitation # 140G0326Q0218
Solicitation 140G0326Q0218 is a request for quotation from the Department of the Interior for advanced statistical modeling and assistance for the Onyx Ranch State Vehicle Recreation Area. The project requires a contractor to analyze a 289-hectare dataset to identify critical issues and map occurrences of invasive species, fire-prone grasses, and protected species, including the desert tortoise and western Joshua trees. Key deliverables include publication-quality figures, distribution maps, and statistical models developed using ArcGIS and various advanced methodologies such as general linear mixed effects models and k-means clustering. The estimated period of performance is from October 1, 2026, to February 28, 2027, with work performed at the vendor's facility. The award will be based on a tradeoff method, requiring contractors to demonstrate advanced statistical expertise through peer-reviewed publications from the last 15 years and proficiency in complex spatial and non-parametric analysis. Required submission documents include a signed SF 18 form, a firm fixed-price quote, a technical submission detailing qualifications, a list of prior relevant contracts with references, and a SAM UEI. Initial drafts of specific tasks are due within 60 days of award, with model drafts due within 90 days. All deliverables become government property, and invoicing must be submitted based on hourly rates and hours worked. Responses are due to the contracting officer by September 17, 2026, at 1500 PST.
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This contract focuses on leveraging advanced analytics, artificial intelligence, machine learning, statistical inference, and probability modeling to improve decision-making processes within challenging and contested operational environments. It is a subcontract opportunity under the Department of Defense, specifically managed by the FA2004 Aflcmc Daf Pae C3BM C3JK office. The work will primarily be performed in San Diego, focusing on the application of cutting-edge computational techniques to support defense-related missions. Key details include the solicitation closing date of June 23, 2026, with the contract posted on June 8, 2026. The contract falls under the NAICS code 541620, which pertains to environmental consulting services but in this context is related to analytics and modeling expertise. This initiative aims to enhance situational awareness and decision superiority for defense stakeholders by integrating sophisticated AI/ML methodologies and probabilistic models into operational workflows.

General Info

Department of Defense subcontract using AI/ML for improved decision-making in contested environments, closing 6/23/26.

Agency

Department Of Defense → FA2004 Aflcmc Daf Pae C3BM C3JKView Agency

NAICS

541620 - Environmental Consulting ServicesView NAICS

Place of Performance

San Diego, CA, USA

Set-Aside

NONE

Documents

This scope was carved out of C3JK-2026-0001.

The full solicitation package (1 document), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Systems Engineer and Technical Advisor (SETA) Support Request for Information

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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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AgencyDepartment Of Defense → FA2004 Aflcmc Daf Pae C3BM C3JK
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Defense → FA2004 Aflcmc Daf Pae C3BM C3JK
View Agency Profile
Office AddressN/A
ContactsNo contact information available

Full Description

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Application of AI/ML, statistical inference, and probability modeling to enhance decision-making in contested environments.

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