Geo Owl · SDVOSB · Est. 2013

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.

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.

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

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

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

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?

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.