Job description

SAIC is hiring a GEOINT SIGINT Data Scientist to deliver Systems Engineering Technical Advisor (SETA) support for a program based in Chantilly, VA. This role contributes to the National Reconnaissance Office’s (NRO) Ground Enterprise Directorate (GED), which oversees the acquisition and lifecycle management of systems from inception to deployment and operations. As the GEOINT SIGINT Data Scientist, you will support the analysis of complex data to drive strategic mission efforts. The role supports the resolution of operational and systems problems into data‑driven solutions, guides analytic strategy, and advises leadership on mission impact, model risk, and data‑informed tradeoffs across GEOINT, SIGINT, and multi‑INT ground architectures. Job Responsibilities to Include: • Supports exploitation, characterization, and modeling of imagery‑derived data; integrates sensor‑specific metadata, collection geometry, and phenomenology into analytic workflows to improve mission performance assessments. • Supports ingestion, normalization, and fusion of structured and unstructured SIGINT data; evaluates signal quality, collection parameters, and processing pipelines to enhance end‑to‑end ground system reliability. • Develops and evaluates data models that combine GEOINT, SIGINT, and mission‑system telemetry to support cross‑domain situational awareness and enterprise‑level decision‑making. • Supports designing and managing data sets to ensure efficient data flow and interoperability with existing and emerging programs. • Supports the collection and integration of large, complex data sets that meet cross‑organizational requirements, including GEOINT/SIGINT mission data repositories and ground processing systems. • Evaluates data quality, reliability, and efficiency throughout the data lifecycle, including sensor‑specific artifacts, collection constraints, and mission‑system dependencies. • Collaborates with other data scientists, software developers, operators, project managers, and clients to prepare data for predictive modeling across GEOINT and SIGINT mission threads. • Documents internal process improvements to optimize data delivery and automate manual processes within ground enterprise workflows. • Supports testing and validation procedures to ensure operational platforms function correctly, including gathering user feedback, identifying issues, conducting updates, and performing routine quality assurance checks on GEOINT/SIGINT data pipelines. • Supports the development of essential technical documentation for reference and reporting, including processes, system specifications, and modifications related to GEOINT/SIGINT data handling and mission‑system integration. • Supports data compliance with regulations, develops guidance, and promotes ethical use of developed platforms, data repositories, and relevant technical records. Required Education and Experience • Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience; PhD or JD and four (4) years or more experience. Relevant experience may be substituted in lieu of degree. • 5+ years of experience in software engineering with IC, DoD, and/or commercial space architectures, systems, and/or operations. • Hands‑on practical experience with data analytics, machine learning, and statistical methods. • GEOINT and SIGINT experience. • Experience in applying modern techniques in artificial intelligence (AI), data science, machine learning (ML), or statistics. • 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.

Requirements

Must-haves

Supports ingestion, normalization, and fusion of structured and unstructured SIGINT data; evaluates signal quality, collection parameters, and processing pipelines to enhance end‑to‑end ground system reliability.
Develops and evaluates data models that combine GEOINT, SIGINT, and mission‑system telemetry to support cross‑domain situational awareness and enterprise‑level decision‑making.
Supports designing and managing data sets to ensure efficient data flow and interoperability with existing and emerging programs.
Supports the collection and integration of large, complex data sets that meet cross‑organizational requirements, including GEOINT/SIGINT mission data repositories and ground processing systems.
Evaluates data quality, reliability, and efficiency throughout the data lifecycle, including sensor‑specific artifacts, collection constraints, and mission‑system dependencies.
Collaborates with other data scientists, software developers, operators, project managers, and clients to prepare data for predictive modeling across GEOINT and SIGINT mission threads.
Documents internal process improvements to optimize data delivery and automate manual processes within ground enterprise workflows.
Supports data compliance with regulations, develops guidance, and promotes ethical use of developed platforms, data repositories, and relevant technical records.
Required Education and Experience
Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience; PhD or JD and four (4) years or more experience. Relevant experience may be substituted in lieu of degree.
5+ years of experience in software engineering with IC, DoD, and/or commercial space architectures, systems, and/or operations.
Hands‑on practical experience with data analytics, machine learning, and statistical methods.
GEOINT and SIGINT experience.
Experience in applying modern techniques in artificial intelligence (AI), data science, machine learning (ML), or statistics.
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaiml

Platform: oracle-cloud
Effort: medium