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Machine Learning Geospatial Jobs in Arlington, VA

GRVTY

Geospatial Analyst - Mid

Falls Church, VA

... of Machine Learning algorithm training and evaluation. The ideal candidate brings strong multi-INT analytical skills and a passion for applying advanced geospatial tradecraft and data science ...

GRVTY

Geospatial Analyst - Mid

Falls Church, VA · On-site

... Machine Learning algorithm training and evaluation. The role involves leveraging multi-INT data, curating imagery, and applying advanced geospatial tradecraft to solve complex military and ...

GRVTY

Geospatial Analyst - Mid

Falls Church, VA · On-site

$85K - $105K/yr

What Impact You'll Have GRVTY is seeking a motivated and experienced Geospatial Analyst to provide ... Experience working with or developing Machine Learning algorithms for exploiting overhead imagery ...

GRVTY

Geospatial Analyst - Mid

Falls Church, VA

$85K - $105K/yr

What Impact You'll Have GRVTY is seeking a motivated and experienced Geospatial Analyst to provide ... Experience working with or developing Machine Learning algorithms for exploiting overhead imagery ...

Vantor

Applied Geospatial ML Engineer

Herndon, VA · On-site

... machine learning solutions • Engineer and transform diverse data types to support all phases of ... geospatial analytics, signal processing, and computer vision) • Design, implement, and assess ...

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All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in Arlington, VA

Machine Learning Geospatial information

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How much do machine learning geospatial jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for machine learning geospatial in Arlington, VA is $33.53, according to ZipRecruiter salary data. Most workers in this role earn between $26.01 and $38.99 per hour, depending on experience, location, and employer.

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.
What are popular job titles related to Machine Learning Geospatial jobs in Arlington, VA? For Machine Learning Geospatial jobs in Arlington, VA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Geospatial jobs in Arlington, VA look for? The top searched job categories for Machine Learning Geospatial jobs in Arlington, VA are:
What cities near Arlington, VA are hiring for Machine Learning Geospatial jobs? Cities near Arlington, VA with the most Machine Learning Geospatial job openings:
Machine Learning Geospatial jobs near you

Geospatial Analyst - Mid

GRVTY

Falls Church, VA

Full-time

Re-posted 9 days ago

Job description

What Impact You'll Have

GRVTY is seeking a motivated and experienced Geospatial Analyst to provide geospatial and imagery expertise and quantitative analysis to make recommendations that improve data curation and development in support of Machine Learning algorithm training and evaluation. The ideal candidate brings strong multi-INT analytical skills and a passion for applying advanced geospatial tradecraft and data science principles to solve complex military and intelligence challenges. This role will drive solutions that improve the quality, diversity, and representativeness of datasets powering ML model development pipelines.

What You'll be Owning

  • Leverage multi-INT data to curate imagery from emerging capabilities, with curated imagery prioritized for:
    • Creation of labeled data to support the model development pipeline
    • Meeting set criteria and characteristics (e.g., geographic coverage, scene attributes) per customer prioritization
  • Based on the characteristics and limitations of new data, recommend curation strategies and identify data gaps to develop a diverse, representative dataset for Machine Learning model development
  • Identify techniques and methods to conduct data mining and retrieval, applying statistical and mathematical analyses to:
    • Identify trends and solve problems
    • Optimize performance
  • Develop and apply methods by collecting, processing, and analyzing large volumes of data to build and enhance products, processes, and systems
  • Visualize information using a range of tools, scripts, and algorithms to:
    • Create explanatory and predictive models
    • Conduct comparative and alternative analysis to address complex military and intelligence challenges
  • Conduct spatial and spatial-temporal analysis and statistics of data holdings to support imagery curation, utilizing knowledge of:
    • Elevation and terrain datasets
    • Customer-directed prioritization criteria including geographic coverage and scene attributes
  • Exploit imagery and analyze geospatial data utilizing GEOINT tradecraft, critical thinking skills, and data science principles, including tools such as:
    • RemoteView
    • Cedalion
    • ArcGIS Pro
    • Jupyter Notebook
  • Utilize programming, statistics, and visualization methods to glean insights from large and disparate data sources
  • Select methods and practices to conduct multi-INT research, descriptive analyses, and exploitation of intelligence databases and sources
  • Implement technical knowledge of GA tradecraft including GIS analyses such as:
    • Viewshed / Line of Sight (LOS)
    • Mobility and Order of Battle
    • Geospatial Synthesis and Modeling
    • Simulation and Terrain Analysis
    • Spatial Statistics

What You Must Have

  • Active TS/SCI Clearance with the ability to obtain a CI/Poly
  • Experience with imagery analytical products and conducting multi-INT analysis
  • Ability to utilize structured, unstructured, and semi-structured data and visualization tools to exploit data through programming and scripting, including:
    • Advanced geospatial skills
    • Strong understanding of how to apply evolving technology and methodologies to related issues

What Would be Nice to Have

  • Experience working with or developing Machine Learning algorithms for exploiting overhead imagery and/or motion imagery products

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