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Internship Google Earth Engine Jobs (NOW HIRING)

Train and supervise under/graduate student(s), interns, and other project team personnel. * Perform ... Proficiency in geospatial and scientific computing tools (e.g., Python, R, GIS, Google Earth Engine ...

Sr. Data Scientist

Indianapolis, IN · On-site

$110.21 - $121.23/hr

Familiarity with cloud-native geospatial tools (PostGIS on AWS RDS, Google Earth Engine, etc.) (nice to have) * Exposure to spatial data infrastructure (GeoServer, MapServer, Mapbox, Deck.gl) (nice ...

... Google Earth Engine, etc.) to automate scientific processes of SAR imagery data to aid analysis * Exhibit a deep understanding of the principles of remote sensing and imagery processing and advanced ...

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How much do internship google earth engine jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for internship google earth engine in the United States is $16.65, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $18.51 per hour, depending on experience, location, and employer.

What is an internship in Google Earth Engine?

An Internship in Google Earth Engine is a temporary position where students or recent graduates work with Google’s cloud-based geospatial processing platform. Interns typically assist with analyzing satellite imagery, developing geospatial applications, and supporting environmental or research projects. This role helps interns gain valuable experience in remote sensing, programming, and data analysis, while contributing to real-world solutions using Google Earth Engine. Interns often collaborate with experienced engineers, researchers, and other professionals, making it a great learning opportunity.

What types of projects do interns typically work on during a Google Earth Engine internship?

As a Google Earth Engine intern, you can expect to work on projects involving large-scale geospatial data analysis, development of tools or scripts for environmental monitoring, or collaborating with external partners on research initiatives. Interns often contribute to real-world solutions, such as mapping deforestation, monitoring urban growth, or developing visualizations for climate data. You'll typically work closely with experienced engineers, data scientists, and researchers, gaining exposure to both the technical and collaborative aspects of the platform. This hands-on experience helps build valuable skills in cloud computing, remote sensing, and data visualization.

What are the key skills and qualifications needed to thrive as an internship in Google Earth Engine?

To succeed in a Google Earth Engine internship, you need a solid background in remote sensing, geospatial analysis, and programming languages like Python or JavaScript, often supported by ongoing or completed studies in geography, environmental science, or computer science. Familiarity with the Google Earth Engine platform, GIS software (such as QGIS or ArcGIS), and data visualization tools is typically required. Strong analytical thinking, problem-solving abilities, and effective communication help you interpret results and collaborate within diverse project teams. These skills are crucial for efficiently processing geospatial data, deriving valuable insights, and contributing to impactful environmental or societal projects.

What is the difference between Internship Google Earth Engine vs Data Analyst Intern?

AspectInternship Google Earth EngineData Analyst Intern
Required SkillsBasic programming, GIS, remote sensing, Google Earth Engine platform knowledgeData analysis, Excel, SQL, visualization tools
Work EnvironmentEnvironmental, geospatial, remote sensing projectsBusiness, finance, marketing, or research sectors
Industry UsageGeospatial analysis, environmental monitoring, climate studiesData interpretation, reporting, decision support

Internship Google Earth Engine focuses on geospatial data analysis using Google Earth Engine, ideal for environmental and remote sensing projects. In contrast, Data Analyst Interns work with broader data sets across industries, emphasizing data interpretation and visualization. Both roles require analytical skills but differ in technical tools and industry focus.

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Infographic showing various Internship Google Earth Engine job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, and 5% Contract. Highlights an 68% Physical, 4% Hybrid, and 28% Remote job distribution, with an average salary of $34,624 per year, or $16.6 per hour.

Tango Sierra-Bravo - Electro‑Optical (EO) Imagery Data Scientist

Select Search Associates LLC

Arlington, VA • On-site

$120 - $180/hr

Other

Posted 9 days ago


Job description

Tango Sierra-Bravo - Electro‑Optical (EO) Imagery Data Scientist
  • Arlington, VA

Join a R&D program that is focused on usingArtificial Intelligence/Machine Learning (AI/ML) algorithms and models, particularly Computer Vision, applied to Intelligence, Surveillance, and Reconnaissance (ISR) sensors and platforms for object detection, object tracking, object classification, and pattern detection. The program isinvolved in developing, testing, fielding, and integrating Computer Vision models for geospatial data.Your job will be to process and condition the geospatial data, and to format it to specific standards so that it can be used for AI solution development. The background that we are looking for is twofold - Data Science experience and deep experience with EO imagery (electro-optical).You will get to join a highly functioning team to develop cutting edge solutionsfor complex problems.

Requirements:
  • Strong background in data scienceWITHexperience in at least one of the following: remote sensing, image processing, or image science
    • At least 4 years of experience with EO imagery…an understanding of collection, phenomenology, image formation process, and exploitation products
  • Background with electromagnetic spectrum (e.g., electro-optical) exploitation to detect occurrence and location of objects
  • Ability to develop, test, and evaluate new algorithms, processes, methodologies, and products using EO imagery including experience utilizing advanced processing tools (e.g., Python, MATLAB, Google Earth Engine, etc.) to automate scientific processes of EO imagery data to aid analysis.
  • Communication skills that allow you to engage with a variety of technical and non-technical audiences on availability and capabilities of EO imagery products, methodologies, procedures, and algorithms to enhance analysis.
  • Strong understanding of the principles of remote sensing and imagery processing and advanced exploitation methods
  • TS/SCI with CI Poly (we can pipeline your poly if you don’t already have it, but you must be willing to take the exam)
  • 13 years of relevant experience and a Master’s degree
    • (substitutions are allowed for different types of degrees, and many things can be applied towards experience – e.g., internships, certifications, professional publications, etc. )
What You Will Do:
  • Obtainnew data and identify potential latency associated with acquisition, data formats, and security domains
  • Pre-process and standardize data to match existing data standards or transform into a usable state for labeling and model testing purposes
  • Interactwith SAR Imagery Scientists to provide coincident EO imagery
  • Identify potential differences between new sensor characteristics and capabilities compared to currently utilized platforms
  • Identifypotential differences in metadata, data format, and data structure characteristics regarding changes to databases, schemas, APIs, and other ETL-related processes for the ingestion and movement of data when integrating into the existing data operations pipeline
  • Determine if there aregaps in thenewly obtained GEOINT or sensor datathat may need to be supplemented by other sources
Bonus Skills:
  • Experience applying CV and machine learning (ML) techniques to EO imagery and data to address intelligence problems
Other Information:
  • Occasional travel may be required outsideof the DC area to support events or exercises
  • Local travel may be required to attend meetings at government facilities
  • Surge support may be needed at times to support crisis situations
  • Work is located at CTR facility
  • Work schedule is flexible, but a good amount of team collaboration is required which generally occurs M-F from 0900-1500 EST and team members should do their best to be reachable during those core hours
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