Data Scientist

SAICChantilly, VA
Onsite

About The Position

SAIC is seeking a Data Scientist to provide Systems Engineer Technical Advisor (SETA) services for a critical position on SAIC’s Prime Program, Landmark AOS. Landmark AOS is a large SETA program, supporting the NRO’s Ground Enterprise Directorate (GED), responsible for the acquisition of systems over the complete end-to-end life cycle. All candidates must have an active TS/SCI clearance with Polygraph to be considered for this role. As the Data Scientist, you will provide specialized technical and engineering expertise supporting the acquisition of software services reliant on artificial intelligence and machine learning (AI/ML). SAIC’s client is tasked with leading the integration of mission focused tools to foster increased efficiency, automation and information sharing. You will also assist and advise Government managers responsible for the complete end-to-end life cycle of the customer's Ground Enterprise. You will work side-by-side with the other LANDMARK AOS staff comprised of world class System Engineers, Acquisition Engineers and Domain Experts to lead the customer in acquiring modern processing applications.

Requirements

  • Active TS/SCI clearance with Polygraph

Responsibilities

  • Provide data collection and analysis to enable transparency and explainability of AI/ML systems.
  • Provide technical and engineering support to the Government customer to manage machine learning analytics programs; apply knowledge and experience to develop and scale AI/ML models in multiple phenomenologies.
  • Provide software architecture and other technical expertise to support the planning of future systems and architectures, and oversight of development contractors.
  • Apply systems analysis and design methodology assessments to identify technical debt, architectural runway and efficiency trade-offs against current and proposed/desired cloud-based software system design.
  • Develop briefings and documentation material to illustrate features, capabilities and mission use cases for the computer vision tool portfolio, including developing technical roadmaps and the acquisition strategies/documentation to implement them.
  • Facilitate technical and programmatic interchanges; identify and resolve issues; and provide engineering and technical advice to the customer to achieve innovative capabilities for automated machine learning analytics.
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