Data Scientist (EO and SAR)

Geo Owl • Springfield, VA

1d

About The Position

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.

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.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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
• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree