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Gis Machine Learning Jobs in Indiana (NOW HIRING)

Sr. Data Scientist

Indianapolis, IN · On-site

$110.21 - $121.23/hr

Experience with GIS tools such as QGIS, ArcGIS, or equivalent * Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing * Experience applying machine learning ...

Sr. Data Scientist

Indianapolis, IN · On-site

$80 - $88/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Experience with GIS tools such as QGIS, ArcGIS, or equivalent * Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing * Experience applying machine learning ...

Gis Machine Learning information

What is a GIS Machine Learning job?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are common challenges when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

What cities in Indiana are hiring for Gis Machine Learning jobs?

Cities in Indiana with the most Gis Machine Learning job openings:

Sr. Data Scientist

Eightelevengroup

Indianapolis, IN • On-site

$110.21 - $121.23/hr

Other

Posted 13 days ago


Job description

Geospatial Data Scientist

Remote

This is a Remote role.

Compensation: $80 - $88 per hour

ABOUT THE ROLE

Our client is seeking a Geospatial Data Scientist to transform complex spatial data into actionable insights and support product and business decision-making. In this role, you will work across the full geospatial data pipeline—from data ingestion and processing to analysis, modeling, and visualization—and collaborate closely with engineering and product teams to embed spatial intelligence into our platform. You will be responsible for developing and maintaining spatial data models, applying machine learning techniques to spatial problems, and creating compelling visualizations for diverse stakeholders. The ideal candidate thrives in a fully remote, asynchronous environment and brings a solid understanding of geospatial standards, coordinate reference systems, and data quality management.

WHAT YOU'LL DO
  • Design and execute geospatial analyses to support product and business decision-making
  • Build, validate, and maintain spatial data models and pipelines
  • Query and manage geospatial datasets using PostgreSQL with PostGIS
  • Work with geospatial data formats including GeoJSON, Shapefile, GeoTIFF, WKT, and WKB
  • Develop machine learning models with spatial components (clustering, classification, interpolation, etc.)
  • Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholders
  • Collaborate with backend engineers to integrate geospatial features into production systems
  • Evaluate and maintain geospatial data quality, coverage, and accuracy
  • Apply GIS tools (QGIS, ArcGIS, or equivalent) for spatial analysis and visualization
  • Ensure clear communication of geospatial insights in a remote, async environment
  • Maintain familiarity with geospatial standards, coordinate reference systems, and spatial indexing
  • Contribute to spatial data infrastructure and cloud-native geospatial workflows as needed
WHAT YOU BRING
  • 3–6 years of experience in data science, GIS, or a related field
  • Strong proficiency in Python for geospatial data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)
  • Deep experience with PostgreSQL and PostGIS for spatial querying and data management
  • Familiarity with geospatial standards and formats (GeoJSON, Shapefile, GeoTIFF, WMS/WFS, WKT, WKB, etc.)
  • Experience with GIS tools such as QGIS, ArcGIS, or equivalent
  • Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing
  • Experience applying machine learning techniques to spatial problems
  • Ability to communicate findings clearly in a fully remote, async environment
  • Experience with remote sensing or satellite imagery analysis (nice to have)
  • 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 to have)
  • Experience with big geospatial data processing (Apache Sedona, H3, S2) (nice to have)
  • Knowledge of Docker and containerized data workflows (nice to have)
  • Familiarity with CI/CD and version control best practices (nice to have)
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