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# Data Analyst

- **Company:** GeoYeti, LLC
- **Location:** Springfield, VA, United States
- **Salary:** $115,000.0 - $139,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Decision Support Systems, GIS Applications, R (Programming Language), Intelligence Analysis, Python (Programming Language), SQL Databases, Tableau (Software), Software Coding
- **Published:** October 2, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f751b8eda61420b0

## About the Role

* Active TS/SCI clearance
 * Experience preparing, analyzing, and drawing insights from large, complex geospatial datasets using statistical methods
 * Working proficiency in Python, R, SQL, GIS tools, or Tableau
 * Experience building visualizations that communicate results clearly to both technical and non-technical audiences

Desired Qualifications:

 * Background in AI/ML-adjacent work related to imagery analysis or exploitation

## Description

At Bcore, our strength comes from how we deliver impact to the mission. Whether it's architecting critical IT solutions, producing actionable intelligence, or developing cutting edge technology, we succeed because of the expertise, collaboration, and agility of our teams. Our Insight Solutions division delivers intelligence analysis, advanced data science, and strategic decision support. Bcore accelerates decisive advantage for warfighters and intelligence professionals by fusing human insight, rapid-fire engineering, precision-measured outcomes, and relentless grit into mission-ready solutions.
Are you ready to lean into analytic approaches that show customers the power of both technical and methodological innovation? Join our growing team supporting customer missions as a Data Analyst in Springfield, VA or St. Louis, MO.
Responsibilities:
You will support a geospatial imagery program by keeping data holdings clean, compliant, and well understood. That means statistical analysis, building lightweight tools to track pipeline progress, and developing visualizations that help the team see what is happening with the data. The role is mid-level, but the data is not simple. Experience with geospatial datasets and a comfort with writing code to solve analytical problems will go a long way here.