Data Scientist (EO and SAR)

Geo Owl

$100K — $130K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Active TS/SCI clearance
  • Minimum of 10 experience points required
  • Experience with AI/ML technologies and data systems
  • Proficient in geospatial file formats, JSON, and XML
  • 3+ years in quantitative analysis and data visualization, including ETL with SQL and NoSQL
  • Development skills in Python and related data manipulation languages

Responsibilities

  • Conduct data analysis to assess the impact on ML model development
  • Integrate emerging EO/SAR sensors into data pipelines
  • Build and maintain labeling campaign management tools
  • Develop imagery curation algorithms for data acquisition prioritization
  • Create geospatial visualization tools to enhance existing platforms
  • Support data cleansing and analytical workflows
  • Evaluate training/test/validation splits for effective model development

Benefits

  • Health Insurance (Geo Owl covers 80%+ of premium)
  • 401k matching
  • Dental, Vision, and other supplemental insurance plans available
  • Company-paid short-term and long-term disability and life insurance
  • Peer-to-Peer spot bonuses
  • 120 hours of PTO per year plus federal holidays
  • Fully Paid Military Leave
Full Job Description
Data Scientist (EO and SAR)

NGA MAVEN PROGRAM • EO/SAR • AI/ML DATA SCIENCE • SENIOR

Overhead imagery doesn't label itself - and machine learning models don't build themselves from random data. As the Senior Data Scientist on NGA Maven, you'll bring statistical rigor, geospatial expertise, and software capability together to ensure the EO and SAR data that feeds Maven's models is selected, processed, and partitioned for maximum analytical value.

Role Overview

The Data Scientist performs data analysis via statistical and quantitative methods, develops visualizations to support decision making, and develops software to enable thorough monitoring and management of data pipeline tasks. You'll lead the design and application of methods to identify, collect, process, and analyze large volumes of EO and SAR imagery data - integrating emerging sensors, evaluating training/test/validation data splits, and building the curation and labeling tools that keep Maven's model pipeline moving.

Source-Derived Role Summary

The Data Scientist shall perform data analysis via statistical and quantitative methods, develop visualizations to support decision making, and develop software to enable thorough monitoring and management of data pipeline tasks. Position supports EO and SAR sensor modalities on the NGA Maven program.

A Day in the Life
  • Conduct analysis of Maven data holdings to evaluate impact on ML model development: assess data diversity, training/test/validation splits, and recommend partition strategies for effective model performance evaluation
  • Integrate emerging EO/SAR sensors into Maven pipelines - assessing metadata, format, and schema differences and building the ETL workflows to ingest new data
  • Build and maintain labeling campaign management tools: track unlabeled vs. labeled data, campaign status, and enable API-based transfer of label task information between platforms
  • Develop and apply imagery curation algorithms and analytic tools for acquisition prioritization and chipping - including web scraping for curation per Maven data priorities
  • Build geospatial visualization and filtering tools that integrate with the existing Data Management Platform
  • Apply ETL and statistical methods to support data cleansing, analyst workflow efficiencies, and intelligence requirement fulfillment


Why This Role Matters

Mission Impact

The data science work you do on Maven determines the quality and operational readiness of AI/ML models used for real-world intelligence. How you curate, partition, and analyze training data shapes how well those models perform when it counts.

Geo Owl Impact

Your quantitative rigor and software capability strengthen Geo Owl's technical credibility on Maven and expand our ability to deliver mission-critical data science support across EO and SAR modalities.

Your Growth

You'll develop dual expertise in geospatial AI/ML data science and national security GEOINT - working with both EO and SAR on production ML pipelines where your statistical and engineering decisions have direct operational impact.

Core Responsibilities
  • Integrate emerging EO/SAR sensors into Maven pipelines; assess ETL process changes needed for new metadata, formats, and data structures
  • Lead the design and application of methods to identify, collect, process, and analyze large volumes of data to build and enhance products, processes, and systems
  • Evaluate and recommend solutions for partitioning emerging sensor data into effective training, test, and validation splits for ML model development
  • Build imagery curation algorithms and web-scraping tools per Maven data priorities; integrate multiple data and intelligence sources to address gaps
  • Develop labeling campaign management software tracking unlabeled/labeled data status and enabling API-based movement of label task information between platforms
  • Build tools to filter and visualize data geospatially, enable feedback entry, and integrate with the existing Data Management Platform
  • Conduct analysis of overall Maven data holdings to support development of performant AI/ML models satisfying operational user requirements
  • Evaluate, monitor, and recommend ways to partition training, test, and validation splits for effective model development and performance evaluation


Required Qualifications
  • Active TS/SCI clearance
  • Minimum 10 experience points required (see experience point calculation below)
  • Experience working with AI/ML technologies and data systems
  • Experience working with multiple file types including geospatial file formats, JSON, and XML
  • 3+ years of experience performing quantitative analysis, developing visualizations, and processing complex data to create data-driven insights; includes data manipulation and ETL experience with SQL and NoSQL
  • Development experience in Python and other languages for data cleaning and manipulation


Preferred Qualifications
  • Experience applying NLP algorithms to extract data from documents
  • Experience with NGA analytic modernization efforts: SOM, computer vision, automated collection, or automated reporting; familiarity with data standardization best practices
  • Demonstrated expertise in math, statistics, and quantitative analysis; experience with classification, regression, clustering, data reduction, and causal modeling techniques


Experience Point Requirement

This is a Senior-level (Level 4) position requiring a minimum of 10 experience points. Points are calculated as follows:
  • Education: Associate's = 2 pts • Bachelor's = 3 pts • Master's = +2 pts • PhD = +3 pts
  • Professional / Military Experience: 1 pt per year of relevant experience
  • Certifications: 0.5 pts each
  • Specialized Training: 0.25 pts per relevant course
  • Professional Impact (publications, presentations, patents): up to 3 pts total


Tools, Technologies & Tradecraft

Python SQL / NoSQL AI/ML Technologies EO/SAR Data Geospatial File Formats JSON / XML ETL Pipelines Data Visualization NLP [Preferred] Computer Vision [Preferred] Statistical Modeling [Preferred]

What Makes Someone Successful in This Role
  • You think statistically about data - you understand why training/test/validation splits matter and you design them with model performance in mind
  • You build software that other people can use - your tools are reliable, documented, and integrate cleanly with existing platform infrastructure
  • You're comfortable with ambiguity around emerging sensors - you can assess an incomplete spec, make sound assumptions, and build toward a workable solution
  • You treat data curation as science - you understand how imagery diversity, geographic coverage, and scene characteristics affect model generalizability
  • You foster cross-team collaboration - you share methods, explain your reasoning, and help the broader team work more efficiently


Is This Role For You?
• Great Fit

You are a data scientist with applied AI/ML experience who wants to work on geospatial problems with national security stakes. You're equally comfortable writing quantitative analysis and building pipeline tools - and you want your work to feed directly into model development that matters operationally.

✘ May Not Be For You

This may not be the right fit if you prefer model-building or inference work over data curation and pipeline engineering, or if geospatial file formats and sensor phenomenology feel outside your area of interest.

Career Growth & Professional Value

This role develops advanced data science expertise at the intersection of geospatial AI and national security - a domain where practitioners with both quantitative depth and systems-level pipeline experience are genuinely scarce. You'll build hands-on experience with EO and SAR data, production ML data operations, and NGA enterprise tooling in a cleared environment.

Benefits:

Health Insurance (Geo Owl pays 80%+ of the premium).

401k matching.

Dental, Vision, and other supplemental insurance plans available.

Company-paid short-term and long-term disability and life insurance.

Peer-to-Peer spot bonuses.

120 hours of PTO per year plus federal holidays.

Fully Paid Military Leave: *You make your full Geo Owl salary while you are on military duty*

Exiting the Military? Apply to our Military Transition Program for key insights into making the transition to civilian life from people who have been there before!

Engage with Your Team!

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