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Geospatial Data Science Intern Jobs in St Louis, MO

NV5

Geospatial Database Administrator

Saint Louis, MO · On-site

Geospatial Data Administration: * Work with Data Manager to develop and execute complex spatial ... Bachelor's degree in GIS, Geography, Computer Science, or a related field. * Equivalent experience ...

GRVTY

Senior Data Scientist

Saint Louis, MO · On-site

Familiarity with geospatial data science, GEOINT workflows, or multi-INT analysis. What Would Be Nice to Have * Experience with additional programming languages or low-code/no-code platforms such as ...

GRVTY

Senior Data Scientist

Saint Louis, MO · On-site

Familiarity with geospatial data science, GEOINT workflows, or multi-INT analysis. What Would Be Nice to Have * Experience with additional programming languages or low-code/no-code platforms such as ...

GRVTY

Senior Data Scientist

Saint Louis, MO · On-site

Familiarity with geospatial data science, GEOINT workflows, or multi-INT analysis. What Would Be Nice to Have * Experience with additional programming languages or low-code/no-code platforms such as ...

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Geospatial Data Science Intern information

See St Louis, MO salary details

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How much do geospatial data science intern jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for geospatial data science intern in St. Louis, MO is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 per hour, depending on experience, location, and employer.

What is a geospatial data science intern?

A Geospatial Data Science Intern helps analyze and interpret spatial data using GIS, statistical methods, and machine learning. They work with mapping tools, databases, and coding languages like Python or R to extract insights from geographic information. Interns may assist in data collection, visualization, and model development for applications in urban planning, environmental science, transportation, and more. This role provides hands-on experience with geospatial technologies and real-world problem-solving.

What types of projects or tasks can a geospatial data science intern expect to work on?

As a Geospatial Data Science Intern, you may assist with tasks such as cleaning, analyzing, and visualizing geospatial datasets, creating maps and spatial models, or developing scripts to automate data processing workflows. Interns often support research projects related to urban planning, environmental analysis, logistics, or public health, depending on the industry and team focus. You'll likely work closely with a mix of data scientists, GIS analysts, and subject matter experts, gaining exposure to real-world applications of spatial data. This hands-on project work can help build your portfolio and provide valuable experience that supports future career growth in geospatial science and analytics.

What are the key skills and qualifications needed to thrive as a geospatial data science intern?

To thrive as a Geospatial Data Science Intern, you need a background in data science, spatial analysis, and GIS concepts, ideally supported by coursework or a degree in geography, computer science, or a related field. Familiarity with tools such as ArcGIS, QGIS, Python, SQL, and data visualization platforms is commonly expected, while knowledge of remote sensing or geospatial databases is a plus. Problem-solving abilities, attention to detail, and strong communication skills help interns excel in collaborative, project-driven environments. These skills are crucial for effectively analyzing spatial data and successfully contributing to innovative geospatial solutions.

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For Geospatial Data Science Intern jobs in St. Louis, MO, the most frequently searched job titles are:

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Geospatial Data Science Intern jobs near you
Infographic showing various Geospatial Data Science Intern job openings in St. Louis, MO as of August 2026, with employment types broken down into 42% Internship, and 58% Full Time. Highlights an 49% In-person, and 51% Remote job distribution, with an average salary of $45,509 per year, or $21.9 per hour.

Senior Geospatial Data Engineer

Object Computing, Inc.

Saint Louis, MO • On-site

$103K - $140K/yr

Full-time

Re-posted 11 days ago

Job description

Object Computing, Inc. is seeking a Senior Geospatial Data Engineer to join our Xtrack Product Team. In this role, you will lead the design and implementation of scalable, cloud-based geospatial data infrastructures, and play a key part in shaping our data architecture and product engineering strategy with a focus on improving safety and operational efficiencies for organizations in the rail industry. You will work with cutting-edge technologies in image processing, artificial intelligence, cloud computing, and geospatial database management. Your work will optimize complex business processes and unlock new value from large-scale geospatial datasets.
What you will do:
  • Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience.
  • Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data.
  • Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products.
  • Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication.
  • Translate complex analytics and business questions into actionable, production-grade data solutions.
  • Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products.
  • Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure).
  • Ensure data quality, integrity, and security across all stages of the data lifecycle.
  • Mentor and provide technical guidance to junior data engineers and team members.
  • Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership.
  • Proactively recommend and implement improvements to existing data infrastructure and software programs.
  • Stay current with industry trends and emerging technologies in geospatial data engineering.
What you will bring:
  • An excitement and dedication towards manifesting real and measurable impact for customers and clients and a dedication to being a team player towards achievement of those outcomes.
  • Experience in software development, data engineering, or big data roles, preferably with a focus on geospatial data.
  • Experience building solutions with Python.
  • Experience with relational databases (e.g., SQL), including advanced query building, data extraction, and manipulation.
  • Experience architecting and optimizing cloud-based data solutions (preferably GCP, AWS, or Azure).
  • Deep experience with big data technologies such as Hadoop, Spark, MapReduce, or Kafka.
  • Experience integrating with API-driven, service-to-service web services.
  • Demonstrated ability to lead projects, mentor team members, and drive technical decisions.
  • Strong problem-solving skills, resourcefulness, and ability to work independently or collaboratively.
  • Excellent organizational, interpersonal, and communication skills.
What will make you stand out:
  • Expertise with geospatial libraries and tools (e.g., GDAL, PDAL, PostGIS, GeoPandas, Shapely).
  • Experience deploying and scaling machine learning (ML) models/algorithms in production.
  • Strong experience with geospatial analytics and working with geospatial data formats (e.g., LAS, LAZ, COPC, GeoTIFF, Shapefiles).
  • Experience leading teams in integrating and scaling complex ML/Deep Learning (DL) algorithms.
  • Experience working with LiDAR data and deriving real-world insights from point clouds.
  • Experience with ESRI products (ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise) or other GIS platforms.
  • Experience with data streaming, real-time data processing, or cloud-native geospatial solutions.
  • Cloud certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Data Analytics).
  • Experience with OAuth, authentication, and API key management for secure service-to-service communication.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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