Geospatial Data Scientist (TS/SCI)

Vantor•Springfield, VA

2d•$140,000 - $205,700•Onsite

About The Position

Vantor is seeking a Geospatial Data Scientist to provide technical expertise for customer projects involving dynamic geospatial information, including non-traditional GEOINT, OSINT, SIGINT, and foundational intelligence data. The role involves fusing multiple sources of information into key findings and performing geo-temporal pattern-of-life analysis to meet customer requirements. As a team member, you will closely support mission partners, with your work having a direct impact on mission imperatives. You will collaborate with software developers, data analysts, data scientists, and subject matter experts.

Requirements

Must have a current/active TS/SCI and be willing and able to obtain a CI polygraph.
At least 10 years of experience as a data analyst, data scientist or similar.
Experience working with a scripting language like Python, SQL, or similar.
In-depth knowledge of technical data types based on previous research and work with data protocols of interest. Data types of interest include Technical Telemetry Data and other forms of telecommunication protocol data types, including cellular, wi-fi, and ethernet.
Experience performing data analysis for the purposes of working with partners to help inform and scale their analytics.
Must be able to work on-site in Springfield, VA.

Nice To Haves

Comfortable briefing senior level leaders.
Experience conducting Activity-Based Intelligence or Pattern of Life analysis.
Experience creating new and innovative analytical workflows and methodologies and creating scalable solutions for existing workflows.
Experience in a customer facing role.
Experience with Spark, Pyspark, or Spark SQL.
Experience working with Jupyter Notebooks.
Experience working with other intel analysts and/or special operations customers.

Responsibilities

Ingesting, spatially processing, applying targeting analytics, and enabling further correlation to other datasets in our on-prem HPC utilizing internal and external tools.
Scaling analytics for pattern-of-life development.
Enabling ingest and spatial processing of internal and external data sources.
Developing spatial analytics within our big data science environment to perform correlations at scale, across multiple data types for further discovery and processing.
Working with internal and external customers to refine code, develop new analytics and new methodologies to export points and places-of-interest to customers and partners.
Creating and applying automation workflows to better enable current AAP tools (Mosaic, Quantum Horizon and BDSE) to better support CPAAC customers and partners.