Data Science Support for Passenger Throughput Optimization

This contract seeks to apply data science methodologies to model passenger flow and checkpoint throughput at Transportation Security Administration screening locations, with the goal of improving staffing allocation and overall operational efficiency. The work will involve analyzing large-scale transportation data to identify bottlenecks, predict demand patterns, and develop predictive models that support real-time decision-making for TSA personnel. The contractor will be expected to deliver scalable analytical tools and actionable insights that directly inform staffing schedules, resource deployment, and process adjustments to reduce wait times and enhance security effectiveness. The opportunity is structured as a subcontract under the North American Industry Classification System code 541690, which covers other scientific and technical consulting services, and is managed by the Science and Technology Acquisition Division of the Department of Homeland Security. Proposals must be submitted by May 12, 2026, with no set-aside designation specified. While no point of contact or physical location for performance is provided, the project is inherently tied to TSA screening operations across the United States, requiring close collaboration with federal security personnel and the integration of real-world operational constraints into the modeling framework. Success will be measured by the ability to translate data-driven recommendations into measurable improvements in passenger throughput and staffing optimization.