Geospatial Data Scientist / Machine Learning Engineer (TS clearance)

Figure Eight Federal; Arlington (VA); On-site; USD 114,000 - 185,000; Full time

Job summary

A leading company in AI training data seeks a Geospatial Data Scientist / Machine Learning Engineer. This pivotal role bridges geospatial data expertise and machine learning applications, requiring substantial experience, programming skills, and an active top secret security clearance.

Qualifications

• 3+ years of experience with remote sensing data in analytical applications.
• Strong programming skills in Python or R required.
• Knowledge of EO, IR, and SAR sensing phenomenologies.

Responsibilities

• Analyze and process geospatial datasets from multiple sensing modalities.
• Develop and implement strategies for geospatial machine learning.
• Stay current with emerging trends in remote sensing.

Skills

Python

R

Geospatial Data Analysis

Machine Learning

Data Visualization

Education

Bachelor's degree in Remote Sensing

Master's degree in Remote Sensing

Tools

GDAL

GeoPandas

TensorFlow

PyTorch

Job description

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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
• Other duties as assigned
  
  
  

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)
  
  
  

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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