Figure Eight Federal (F8F): Leading the Future of AI Training Data Figure Eight Federal (F8F) provides accurate and reliable human annotated datasets that fuel AI and machine learning for some of the world’s biggest brands.  With more than 25 years of industry knowledge, F8F’s technology powers many of the AI interactions we experience every day. Our solutions and expertise empower our clients to achieve their AI goals and make a significant impact in their industry. We are seeking an exceptional Geospatial Data Scientist (GDS) to join our team at the cutting edge of data focused geospatial analytics. This role sits at the critical intersection of remote sensing, computer vision, machine learning, and data science. The ideal candidate will possess advanced knowledge of raster-level geospatial data, comprehensive understanding of collection metadata, and expertise in various sensing phenomenologies including Electro-Optical (EO), Infrared (IR), and Synthetic Aperture Radar (SAR). This position is pivotal in bridging the gap between geospatial data expertise and machine learning applications.  Responsibilities:

Analyze and process complex geospatial datasets from multiple sensing modalities (EO, IR, SAR) 

Evaluate dataset quality, coverage, and metadata to determine suitability for ML applications 

Develop and implement innovative data preparation strategies for geospatial machine learning 

Design and execute validation methods for geospatial data quality assurance 

Develop automated processes for geospatial data integration and harmonization 

Generate comprehensive documentation of data characteristics, limitations, and potential biases 

Stay current with emerging trends and technologies in remote sensing and geospatial data science 

Provide technical consultation on remote sensing capabilities and limitations for project planning 

Qualifications:

Bachelor's degree in Remote Sensing, GIS, Computer Science, Geospatial Science, Data Science, or related field (additional years of experience may be substituted for degree)

3+ years of experience working with remote sensing data in analytical applications 

Demonstrable knowledge of EO, IR, and/or SAR sensing phenomenologies and their unique characteristics 

Strong programming skills in Python or R, with experience using geospatial libraries (e.g., GDAL, GeoPandas) 

Working knowledge of computer vision techniques applied to satellite/aerial imagery 

Proficiency with geospatial metadata standards and their importance in analysis 

Experience evaluating dataset suitability for ML training and deployment 

Experience with containerization (Docker) and workflow automation for geospatial pipelines 

Strong ability to visualize data for consumption by both technical and non-technical audiences 

Active Top Secret security clearance 

Preferred Qualifications:

Master's degree in Remote Sensing, Computer Science, Geospatial Science, Data Science, or related field 

Experience with machine learning frameworks (TensorFlow, PyTorch) and their application to geospatial data 

Experience with GIS tools such as QGIS, ArcGIS, etc. 

Knowledge of deep learning architectures specifically designed for remote sensing data 

Familiarity with hyperspectral and LiDAR data processing 

Experience with time-series analysis of satellite imagery 

Understanding of uncertainty quantification in geospatial data and propagation into ML models 

Experience with cloud-based geospatial computing (AWS, Google Earth Engine, Microsoft Planetary Computer)