Exploitation Specialist​/Data Scientist 11

• Falls Church, VA

Overview
We are seeking an experienced
Exploitation Specialist/Data Scientist
to join a high-performing team supporting advanced AI and machine learning initiatives for complex national security and intelligence missions.
This program focuses on evaluating AI models against Government datasets to assess their performance, resilience, and robustness across a broad spectrum of adversarial scenarios. The effort also includes testing and validating autonomous algorithms designed to support operational decision-making in dynamic mission environments.
As a Data Scientist, you will play a key role in designing, implementing, and maintaining the data architecture that supports AI/ML model development, testing, and evaluation. You will develop scalable data pipelines, integrate data from emerging sensors and platforms, and ensure data is standardized, accessible, and compliant with Government data governance requirements. Working closely with engineers, imagery scientists, and mission analysts, you will help deliver reliable, high-quality datasets that enable advanced analytics and operational decision-making.
Required Qualifications

• 9+ years of relevant experience in data science, automation, software development, data engineering, database integration, GEOINT support, or related technical disciplines. A combination of education, professional certifications, and technical training may be considered in lieu of some years of experience.
• Proficiency in Python and its data science and visualization ecosystem, including Pandas, Num Py, Sci Py, Matplotlib, Plotly, Dash, Bokeh, and related libraries.
• Demonstrated experience connecting multiple databases and enterprise systems to automate data collection, transformation, and dissemination.
• Experience automating repetitive business or analytic tasks using scripts and workflows.
• Experience gathering and disseminating metrics and operational data.
• Demonstrated ability to identify process inefficiencies and implement automation solutions that improve workflow performance.
• Strong analytical and problem-solving skills.
• Effective written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.

Preferred Qualifications

• Experience supporting NGA enterprise technologies and environments, including
  NGA CORE
  ,
  NGA MLOps
  , Government Authority to Operate (ATO) processes, and Government Non-Person Entity (NPE) certificates.
• Experience implementing processes and tools within organizations utilizing the
  Scaled Agile Framework (SAFe).
• Experience developing dashboards and data visualizations to monitor operational pipeline health, data availability, currency, throughput, and overall system performance.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines to ingest, process, and store data from emerging sensors and collection platforms.
• Create and manage database schemas, tables, and supporting infrastructure while implementing automated data quality monitoring and health alerts.
• Develop API-based workflows to securely move sensor data between Government data platforms in accordance with program requirements.
• Ensure all sensor data complies with Government-defined schemas, formatting standards, metadata requirements, and data governance policies.
• Assess the impact of new sensor data on existing databases, metadata models, APIs, schemas, and ETL processes to support seamless integration into operational data pipelines.
• Develop preprocessing and standardization workflows to prepare data for AI/ML model training, testing, and evaluation. Activities may include format conversion, imagery chipping, orthorectification, metadata normalization, and other transformation processes required to produce high-quality analytical datasets.
• Collaborate with cross-functional teams to optimize data workflows, improve pipeline reliability, and support the delivery of mission-ready datasets for advanced analytics and machine learning applications.

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