Data Scientist

Data Scientist providing Systems Engineer Technical Advisor (SETA) services for AI/ML-enabled software acquisition on the Landmark AOS program, supporting the NRO Ground Enterprise across the end-to-end lifecycle. This on-site role is based in Chantilly, VA and offers a salary range of USD 160,001 - 200,000 per year. A Master's degree is required.

Summary

The Data Scientist delivers SETA support for AI/ML-enabled software acquisitions on the Landmark AOS program, assisting the NRO Ground Enterprise throughout the full lifecycle from planning to deployment.

Responsibilities

• Collect and analyze data to support transparency and explainability of AI/ML systems.
• Provide technical and engineering support to the Government customer for managing machine learning analytics programs; apply expertise to develop and scale AI/ML models across multiple phenomenologies.
• Deliver software architecture guidance and other technical insight to help plan future systems and architectures, including oversight of development contractors.
• Apply systems analysis and design methodology to identify technical debt, establish architectural runway, and evaluate efficiency trade-offs against current and proposed cloud-based software designs.
• Create briefings and documentation illustrating features, capabilities and mission use cases for the computer vision tool portfolio; develop technical roadmaps and acquisition strategies with supporting documentation to implement them.
• Coordinate technical and programmatic interchanges, identify and resolve issues, and provide engineering and technical guidance to enable innovative automated machine learning analytics.
• Collaborate closely with LANDMARK AOS staff, including System Engineers, Acquisition Engineers and Domain Experts, to guide the customer in acquiring modern processing applications.

Requirements

• Education and experience: Bachelor's degree with 2+ years of related experience, or Master's degree with 0 years related experience.
• Active Top Secret clearance with polygraph.
• Strong engineering foundation 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 initiative, creative problem-solving and critical thinking abilities.
• Proven capability and success working in team environments.
• Strong oral and written communication skills on significant technical matters requiring coordination in a high-tempo environment.
• Proficiency with MS Office applications.

Technologies

• MS Office