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Machine Learning Geospatial Jobs in Mesquite, TX

Techvilla Solutions

Data Scientist

Carrollton, TX

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ...

Techvilla Solutions

Data Scientist

Desoto, TX

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ...

Techvilla Solutions

Data Scientist

Garland, TX · On-site

Expertise in statistical modeling, machine learning, and predictive analytics. * Strong proficiency ... Strong expertise in geospatial analytics and LiDAR data processing. * Hands-on experience with ...

Gigapower

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

... geospatial or OSP platforms such as Esri and ArcGIS. • Experience preparing, modeling, and optimizing data for AI, machine learning, and retrieval-augmented generation (RAG) use cases. • ...

Gigapower

Data Engineer

Dallas, TX · Remote

$117K - $140K/yr

... with geospatial or OSP platforms such as Esri and ArcGIS. · Experience preparing, modeling, and optimizing data for AI, machine learning, and retrieval-augmented generation (RAG) use cases. · ...

IT America Inc

Full Stack Developer

Dallas, TX · Remote

Deploy, scale, and monitor machine learning workloads on AWS (SageMaker, Lambda, or ECS ... Experience in healthcare analytics or geospatial applications (preferred). * Strong problem-solving ...

Motorola

Senior DevOps Engineer (US REMOTE)

Allen, TX · Remote

$140K - $170K/yr

The solutions we create apply exciting technologies such as geospatial visualization and analytics ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

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All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in Mesquite, TX

Machine Learning Geospatial information

See Mesquite, TX salary details

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How much do machine learning geospatial jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for machine learning geospatial in Mesquite, TX is $26.49, according to ZipRecruiter salary data. Most workers in this role earn between $20.53 and $30.82 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 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 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 job categories do people searching Machine Learning Geospatial jobs in Mesquite, TX look for?

The top searched job categories for Machine Learning Geospatial jobs in Mesquite, TX are:

What cities near Mesquite, TX are hiring for Machine Learning Geospatial jobs?

Cities near Mesquite, TX with the most Machine Learning Geospatial job openings:

Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in Mesquite, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $55,104 per year, or $26.5 per hour.

Data Scientist

Techvilla Solutions

Carrollton, TX

Full-time

Posted 17 days ago

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.

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