Data Engineer

KBR•Chantilly, VA

11d

About The Position

The Data Scientist supports advanced analytics and data-driven decision-making for Space and Counterspace intelligence missions. This role focuses on developing models, algorithms, and analytical tools to extract insights from large, complex, and multi-source datasets related to space domain awareness and adversary capabilities. The position involves working with both structured and unstructured data to identify patterns, anomalies, and emerging threats. The Data Scientist collaborates with analysts, engineers, and mission partners to translate intelligence questions into scalable analytic solutions. This role operates in a classified environment supporting national security objectives with cutting-edge data science techniques.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
Experience in data science, analytics, or a related technical discipline (academic research and internships may be considered)
Proficiency in programming languages such as Python or R
Experience with data analysis libraries and tools (e.g., Pandas, NumPy, SciPy, or similar)
Active Top Secret/SCI security clearance With Polygraph
Strong software development background (Python, R, Java)
Experience with containerization and orchestration (Docker, Kubernetes)
Familiarity with software development lifecycle (SDLC) practices
API design and development experience
Test-driven development or equivalent quality practices

Nice To Haves

Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-learn)
Familiarity with big data platforms and tools (e.g., Hadoop, Spark, or distributed computing environments)
Exposure to geospatial analytics, space domain awareness, or intelligence-related datasets
Astrodynamics or orbital mechanics familiarity (or experience with STK)
Time-series analysis
NLP/text analytics
Cloud platforms (AWS GovCloud)
Containerization (Docker, Kubernetes)
CI/CD and DevSecOps experience
Experience with IC data environments or tools
Experience transitioning prototype models to operational production pipelines

Responsibilities

Develop and implement statistical models, machine learning algorithms, and data analysis workflows to support mission objectives
Analyze large, complex datasets from multiple intelligence sources to identify trends, anomalies, and actionable insights
Build and maintain data pipelines, data transformation processes, and analytic tools
Support integration of disparate data systems to enable comprehensive analysis across domains
Develop visualizations, dashboards, and reporting tools to communicate analytic findings
Apply data mining, predictive analytics, and pattern recognition techniques to space and counterspace problems
Collaborate with engineers and analysts to refine requirements and operationalize data science solutions
Document methodologies, models, and processes for reproducibility and mission continuity
Ensure compliance with security, data governance, and classified environment requirements
Perform code review and software quality testing
Review and utilize RESTful APIs for data access
Apply software design patterns, code review practices, and unit/integration testing
Build and maintain CI/CD pipelines for data infrastructure
Contribute to infrastructure-as-code (Terraform, Ansible)