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Company: SAIC
Location: Chantilly, VA
Career Level: Entry Level
Industries: Technology, Software, IT, Electronics

Description

Description

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 in Chantilly, VA. 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.

As a Data Scientist, you will provide specialized technical and engineering expertise supporting the acquisition of computer vision (machine learning automated target recognition) software services. 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.

Job Responsibilities to include:

  • Provide technical and engineering support to the Government customer to manage computer vision machine learning analytics programs; apply knowledge and experience to develop and scale automatic target recognition models in multiple phenomenology's.   
  • 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.

Qualifications

Required Education and Experience 

  • Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience. Relevant experience to be substituted in lieu of degree. 
  • Active Top Secret Clearance with Polygraph
  • Strong engineering background with knowledge of software architecture and machine learning approaches including computer vision applications 
  • Experience with ontologies, training dataset generation, model evaluation and validation, and responsible AI practices
  • Domain knowledge in Agile software development practices (Scrum, SAFe) and cloud computing architectures with experience monitoring software development progress via agile metrics, identifying risks, discrepancies, and performance issues
  • Demonstrated high level of initiative, creative problem-solving, and critical thinking
  • Demonstrated capability and success working in team environments
  • Strong oral and written communications ability on significant technical matters often requiring coordination within a high-tempo environment
  • Good working knowledge of MS Office applications


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