Senior Data Scientist

CACI InternationalSt. Louis, MO
$82,100 - $172,400Onsite

About The Position

Apply advanced analytics and machine learning to mission problems for the National Geospatial-Intelligence Agency (NGA). Work at the intersection of data science and geospatial intelligence, turning large, complex datasets into decision advantage. Collaborate directly with analysts and mission users to shape analytic capabilities from concept to deployment. Lead data science practices within a multi-team Agile delivery environment.

Requirements

  • Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (equivalent experience accepted).
  • 8+ years of data science, analytics, or related engineering experience.
  • Expert proficiency in Python (or R) for data manipulation, modeling, and analysis.
  • Experience developing and deploying machine learning models into production environments.
  • Strong SQL skills and experience with large-scale data platforms.
  • Demonstrated experience with data visualization tools and techniques.
  • Security Clearance (TS/SCI) with willingness to undergo polygraph examination.

Nice To Haves

  • Experience with geospatial data (imagery, vector, raster) and geospatial analytics.
  • Familiarity with cloud-based ML services and containerized model deployment.
  • Experience supporting NGA analysts or Intelligence Community mission workflows.

Responsibilities

  • Design, develop, and deploy analytic models and machine learning solutions against large-scale structured and unstructured datasets.
  • Build and automate data processing pipelines for collection, cleaning, transformation, and enrichment.
  • Develop visualizations and analytic products that communicate complex findings to technical and non-technical audiences.
  • Collaborate with mission analysts to translate analytical requirements into deployed software capabilities.
  • Integrate analytic capabilities with program systems and services in coordination with development teams.
  • Evaluate model performance, drive iterative improvement, and document methodologies.
  • Mentor mid-level data scientists and promote analytic best practices across the program.

Benefits

  • flexible time off
  • robust learning resources
  • comprehensive benefits
  • healthcare
  • wellness
  • financial
  • retirement
  • family support
  • continuing education
  • time off benefits
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