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Spatial Data Science Jobs in Texas (NOW HIRING)

Diamondback Energy

Data Science Geologist

Midland, TX · On-site

Diamondback Energy is seeking a Data Science Geologist to bridge traditional earth sciences with ... Leverage GIS and subsurface mapping tools to perform complex spatial analysis and create ...

Diamondback Energy

Data Science Geologist

Midland, TX · On-site

This Data Science Geologist will bridge traditional earth sciences with advanced data science and ... Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and ...

Diamondbackenergy

Data Science Geologist

Midland, TX

This Data Science Geologist will bridge traditional earth sciences with advanced data science and ... Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and ...

CoStar

Land.com - Senior Data Scientist

Austin, TX

... spatial joins Preferred Qualifications: Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science Experience with ...

Staffingine LLC

Drone Data Engineer

Houston, TX · On-site

$109K - $131K/yr

Work closely with data science teams to operationalize AI models on drone data * Systems Cloud ... Knowledge of GIS tools spatial data formats and mapping systems * Cloud Systems * Experience with ...

GDH

GIS ETL Developer

Plano, TX · Hybrid

$55 - $60/hr

Bachelor's degree in Geospatial Science, Geography, Computer Science, or a related area; equivalent professional experience acceptable. * Demonstrated experience working on complex spatial data ...

Permian Resources

GIS Platform Analyst

Midland, TX · On-site

... spatial data pipelines, and ensuring the reliability and integrity of GIS data across the ... BA/BS in Geography, Computer Science, or related field. * 4+ years of progressive GIS employment ...

Permian Resources

GIS Platform Analyst

Midland, TX · On-site

... spatial data pipelines, and ensuring the reliability and integrity of GIS data across the ... BA/BS in Geography, Computer Science, or related field. * 4+ years of progressive GIS employment ...

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Spatial Data Science information

See Texas salary details

$41.5K

$120.9K

$165.4K

How much do spatial data science jobs pay per year?

As of Jun 10, 2026, the average yearly pay for spatial data science in Texas is $120,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

What is spatial data science?

Spatial data science is a field that combines data science techniques with geographic information systems (GIS) to analyze and interpret spatial or location-based data. It involves collecting, processing, and visualizing data that has a geographic or spatial component, such as maps, satellite images, or GPS coordinates. Spatial data scientists use methods from statistics, machine learning, and computer science to solve problems related to urban planning, environmental monitoring, transportation, and more. The insights gained from spatial data science help organizations make better decisions based on the relationships and patterns found in geographic data.

What are the key skills and qualifications needed to thrive as a Spatial Data Scientist, and why are they important?

To thrive as a Spatial Data Scientist, you need a strong background in statistics, geospatial analysis, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases (like PostGIS), and relevant certifications (e.g., Esri Technical Certification) is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are vital soft skills to interpret spatial data and convey insights to stakeholders. These competencies are crucial for extracting actionable insights from complex geospatial datasets and supporting informed decision-making.

What is the difference between Spatial Data Science vs Geospatial Analyst?

AspectSpatial Data ScienceGeospatial Analyst
Required CredentialsDegree in GIS, Geography, Data Science, or related fields; often includes certifications in GIS or data analysisDegree in Geography, GIS, or related fields; certifications in GIS software are common
Work EnvironmentData analysis, modeling, and programming; often in tech or research settingsMapping, data visualization, and GIS software use; typically in government, environmental, or urban planning agencies
Employer & Industry UsageTech companies, research institutions, urban planning, environmental agenciesGovernment agencies, environmental consultancies, urban planning firms

Spatial Data Science focuses on analyzing spatial data using advanced data science techniques, programming, and modeling. In contrast, Geospatial Analysts primarily work with GIS software to create maps and visualize spatial data. While both roles require GIS knowledge, Spatial Data Scientists often have stronger programming and statistical skills, working on complex data analysis projects, whereas Geospatial Analysts focus more on mapping and data visualization tasks.

What are some typical challenges spatial data scientists face when integrating geospatial data from multiple sources?

Spatial data scientists often encounter challenges like inconsistencies in data formats, varying coordinate reference systems, and differences in spatial resolution when integrating geospatial data from multiple sources. Addressing these requires familiarity with data transformation tools and a strong understanding of spatial data standards. Additionally, ensuring data quality and managing large datasets can be complex, so attention to detail and effective use of GIS software are crucial for successful integration.
What are popular job titles related to Spatial Data Science jobs in Texas? For Spatial Data Science jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Spatial Data Science jobs in Texas look for? The top searched job categories for Spatial Data Science jobs in Texas are:
Spatial Data Science jobs near you
Infographic showing various Spatial Data Science job openings in Texas as of June 2026, with employment types broken down into 2% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $120,851 per year, or $58.1 per hour.
Data Science Geologist

Data Science Geologist

Diamondback Energy

Midland, TX • On-site

Full-time

Posted 13 days ago

Job description

Job Summary:
Diamondback Energy is seeking a Data Science Geologist to bridge traditional earth sciences with advanced data science and analytics. This role focuses on automating geological workflows, integrating complex subsurface datasets, and developing predictive and geospatial models to improve reservoir characterization and resource discovery.
Responsibilities:
• Predictive Modeling: Develop and apply machine learning and geospatial models to identify geological features and predict reservoir quality.
• Data Integration: Clean, integrate, and analyze diverse datasets, including seismic, well log, geochemical, rock-based, and petrophysical data.
• Spatial Analysis: Leverage GIS and subsurface mapping tools to perform complex spatial analysis and create interactive geological models and maps.
• Automated Workflows: Design, build, and maintain data pipelines to automate routine geological analysis and reporting.
• Stakeholder Communication: Translate complex technical analyses into clear, actionable insights for technical teams and business stakeholders.
Qualifications:
Required:
• Bachelor’s degree in Geoscience or a related field
• Minimum of 5 years of data geoscience experience
• Proficiency in Python (Pandas, Scikit-learn, PyTorch) or R for statistical analysis
• Expertise in SQL and industry-standard geological databases
• Experience with GIS tools such as ArcGIS or QGIS, and/or 3D subsurface modeling software (e.g., Petrel)
• Strong understanding of machine learning techniques (clustering, regression, anomaly detection) applied to subsurface data
• Ability to visualize and communicate spatial data using tools such as Power BI, Tableau, or Python libraries (Matplotlib, Seaborn)
Preferred:
• Background in Petroleum Engineering
Company:
Diamondback Energy to Acquire Mineral Interests in Midland County Founded in 2007, the company is headquartered in Midland, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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