Data Scientist at SAIC in Chantilly, VA

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.

Note: 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.

Job Responsibilities to include:

• 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

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.

Qualifications

Required Education and Experience

• Bachelors and two (2) years or more experience; Masters and 0 years related experience
• Active Top Secret Clearance with Polygraph
• Strong engineering background with knowledge of software architectures and machine learning approaches
• 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

About the Company

SAIC® is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.

We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.