1

Geospatial Data Scientist Jobs in Dallas, TX (NOW HIRING)

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ... Mentor data scientists and promote best practices in analytics and machine learning. * Support ...

next page

Showing results 1-20

Geospatial Data Scientist information

See Dallas, TX salary details

$37.3K

$121.9K

$195.2K

How much do geospatial data scientist jobs pay per year?

As of Aug 25, 2026, the average yearly pay for geospatial data scientist in Dallas, TX is $121,934.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 per year, depending on experience, location, and employer.

What is a geospatial data scientist?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

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

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

How much does a geospatial data scientist make?

A geospatial data scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, location, and industry. Senior roles or those with specialized skills in GIS tools and programming may earn higher compensation.

Is geospatial data scientist still in demand?

Yes, geospatial data scientists are in high demand due to the increasing use of geographic information systems (GIS), remote sensing, and spatial analysis across industries such as urban planning, environmental management, and transportation. The role often requires skills in programming, data analysis, and tools like Python, R, and GIS software, with strong job growth projected in the coming years.

What are the most commonly searched types of Geospatial Data Scientist jobs in Dallas, TX?

The most popular types of Geospatial Data Scientist jobs in Dallas, TX are:

What are popular job titles related to Geospatial Data Scientist jobs in Dallas, TX?

For Geospatial Data Scientist jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Scientist jobs in Dallas, TX look for?

The top searched job categories for Geospatial Data Scientist jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Geospatial Data Scientist jobs?

Cities near Dallas, TX with the most Geospatial Data Scientist job openings:

Infographic showing various Geospatial Data Scientist job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,934 per year, or $58.6 per hour.

Full-time

This job post has expired 8 days ago. Applications are no longer accepted.


Job description

Required Skills
  • 10+ years of hands-on experience in Applied Data Science, Analytics Engineering, and Systems Modeling.
  • 5+ years of client-facing, consulting, or business development experience delivering analytics solutions.
  • Expertise in statistical modeling, machine learning, and predictive analytics.
  • Strong proficiency with Python, scikit-learn, statsmodels, PyTorch, and TensorFlow.
  • Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques.
  • Strong expertise in geospatial analytics and LiDAR data processing.
  • Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries.
  • Experience working with vector, raster, point-cloud, and sensor datasets.
  • Excellent analytical, communication, and stakeholder management skills.
Roles & Responsibilities
  • Design and develop advanced machine learning and statistical models to solve complex business problems.
  • Build predictive models, time-series forecasting solutions, and causal inference frameworks.
  • Perform feature engineering, data preparation, and advanced sampling techniques for large-scale datasets.
  • Develop geospatial analytics and LiDAR processing solutions using industry-standard tools and libraries.
  • Analyze vector, raster, point-cloud, and sensor data to generate actionable insights.
  • Partner with business stakeholders to scope, design, and deliver data science solutions.
  • Present analytical findings and recommendations to technical and business audiences.
  • Optimize model performance, scalability, and deployment in production environments.
  • Mentor data scientists and promote best practices in analytics and machine learning.
  • Support innovation initiatives through advanced analytics and AI-driven solutions.